This is a data dictionary for the Durham County Social Determinants of Health Data. Please contact Mark Yacoub at mark.yacoub@duke.edu if you would like access to the data.
| Variable Name | Full Name | Description | Data Type | Data Level | Years | Percent Missing | Source | Table | Notes |
|---|---|---|---|---|---|---|---|---|---|
| Unit | Unit | A group or suite of rooms within a building that are under common ownership or tenancy, typically having a common primary entrance | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Add_Number | Address Number | The whole number identifier of a location along a thoroughfare or within a defined community | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| AddNum_Suf | Address Number Suffix | An extension of the Address Number that follows it and further identifies a location along a thoroughfare or within a defined area | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| StN_PreDir | Street Name Pre-Directional | Word preceding the Street Name element that indicates the direction taken by the street from an arbitrary starting point or line, or the sector where it is located | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| StN_PreTyp | Street Name Pre-Type | Word or phrase that precedes the Street Name element and identifies a type of thoroughfare in a complete street name | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| StreetName | Street Name | The element of the complete street name that identifies the particular street (as opposed to any street types, directionals, and modifiers) | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| StN_PosTyp | Street Name Post Type | Word or phrase that follows the Street Name element and identifies a type of thoroughfare in a complete street name | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| StN_PosDir | Street Name Post Directional | A word following the Street Name element that indicates the direction taken by the street from an arbitrary starting point or line, or the sector where it is located | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| County | County | Name of county or county-equivalent where the address is located. Proper-case format with no suffix (i.e. Do not include '. . . County'). For this data set, it is all 'Durham' | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| State | State | Name of the state or state equivalent. For this data set, it is all 'NC' | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Zip_Code | Zip Code | For standard street mail delivery (with a corresponding geographic delivery area), the system of 5-digit codes that identifies the individual USPS Post Office associated with an address | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Inc_Muni | Incorporated Municipality | Name of the incorporated municipality or other general-purpose local governmental unit where the address is located | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Post_Comm | Postal Community Name | A city name for the ZIP code of an address, as given in the USPS City State file | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Longitude | Address Longitude | Address Longitude, derived based on point placement | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| Latitude | Address Latitude | Address Latitude, derived based on point placement | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| NatGrid_Coord | National Grid Coordinates | National Grid Coordinate, derived based on point placement. Useful for GIS work | Cross-sectional | Address | 2017 | 0 | National Address Database | building_units | |
| full_combine | Entire address combined | Cross-sectional | Address | 2019 | 0 | Durham Real Property Database | building_units | ||
| building_type | Building type | Cross-sectional | Address | 2019 | 0 | Durham Real Property Database | building_units | ||
| errors | Property/NAD merge errors | Cross-sectional | Address | 2019 | 0 | Durham Real Property Database | building_units | ||
| tax_year | Tax year | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| parcel_ref | Parcel reference | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| land_use | Land use code | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| tax_district | Tax district code | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| subdivision | Subdivision code | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| neighborhood | Neighborhood code | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| date_sold | Date sold | Cross-sectional | Address | 2019 | 63.5 | Durham Real Property Database | building_units | ||
| sales_amount | Sales amount | Cross-sectional | Address | 2019 | 63.5 | Durham Real Property Database | building_units | ||
| total_value | Total assessed value | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| land_size | Map acres | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| lv_method | Land value method code | Cross-sectional | Address | 2019 | 24.5 | Durham Real Property Database | building_units | ||
| stax_district | Split tax district code | Cross-sectional | Address | 2019 | 98 | Durham Real Property Database | building_units | ||
| lpu_value | Land present use code | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| land_value | Land assessed value | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| year_built | Actual year built | Cross-sectional | Address | 2019 | 34.5 | Durham Real Property Database | building_units | ||
| heated_area | Heated area | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| built_usage | Building usage code | Cross-sectional | Address | 2019 | 35 | Durham Real Property Database | building_units | ||
| improvement | Improvement code | Cross-sectional | Address | 2019 | 34.5 | Durham Real Property Database | building_units | ||
| repair_state | Building condition code | Cross-sectional | Address | 2019 | 34.5 | Durham Real Property Database | building_units | ||
| heat | Heat code | Cross-sectional | Address | 2019 | 34.5 | Durham Real Property Database | building_units | ||
| bathrooms | Number of bathrooms | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| half_bathrooms | Number of half bathrooms | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| bedrooms | Number of bedrooms | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| fireplace | Fireplace present | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| basement | Basement present | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| attached_garage | Attached garage present | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| primary_imp | Primary improvement count | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| imp_value | Primary improvement value | Cross-sectional | Address | 2019 | 22 | Durham Real Property Database | building_units | ||
| EHR_address | Electronic health record access | Cross-sectional | Address | 2019 | 0 | Durham Real Property Database | building_units | ||
| census_tract | Census Tract | An area roughly equivalent to a neighborhood established by the Bureau of Census for analyzing populations. Derived from address longitude and latitude | Cross-sectional | Address | 2019 | 0 | Census Geocoder | building_units | |
| n_ret | Number of returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_single | Filing status is single | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_joint | Number of joint returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_head | Number of head of household returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_dep | Number of dependents | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_ral | Number of refund anticipation loan returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_rac | Number of refund anticipation check returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_elderly | Number of elderly returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| agi | Adjusted gross income | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_total_inc | Number of returns with total income | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_total_inc | Total income amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_wage | Number of returns with salaries and wages | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_wage | Salaries and wages | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_farm | Number of farm returns | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_unemp_comp | Number of returns with unemployment compensation | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_unemp_comp | Unemployment compensation amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_txbl_ss | Number of returns with taxable Social Cecurity benefits | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_txbl_ss | Taxable Social Security benefits amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_item | Number of returns with itemized deductions | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_item | Total itemized deductions amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_alt_min_tax | Number of returns with Alternative Minimum Tax | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_alt_min_tax | Alternative Minimum Tax amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_dep_care_credit | Number of returns with Child and Dependent Care Credit | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_dep_care_credit | Child and Dependent Care Credit amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_child_tax_credit | Number of returns with Child Tax Credit | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_child_tax_credit | Child Tax Credit amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_hc_indiv | Number of returns with Health Care Individual Responsibility Payment | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_hc_indiv | Health Care Individual Responsibility Payment amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_total_tax_pay | Number of returns with total tax payments | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_total_tax_pay | Total tax payments amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_eic | Number of returns with Earned Income Credit | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_eic | Earned Income Credit amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_excess_eic | Number of Returns with Excess Earned Income Credit | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_excess_eic | Excess Earned Income Credit (Refundable) amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_tax_due | Number of returns with tax due at time of filing | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_tax_due | Tax due at time of filing amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| n_overpay | Number of returns with overpayments refunded | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| a_overpay | Overpayments refunded amount | Cross-sectional | Zip code | 2015, 2016 | <1 | IRS Individual Income Tax Statistics | tract_taxes_and_wages | Note the naming conventions by this example column name: n_item_16_b3. The first section is the variable name, n_item, followed by either a 15 or 16 denoting the tax year, and then an income bucket number, ranging from b1 to b6 or aggregate. | |
| ACCESS2 | Current lack of health insurance among adults aged 18-64 | Respondents aged 18–64 years who report having no current health insurance coverage divided by respondents aged 18–64 years who report having current health insurance or having no current health insurance | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| ARTHRITIS | Arthritis among adults aged 18+ years | Respondents aged > or = 18 years who report having been told by a doctor, nurse, or other health professional that they had arthritis divided by respondents aged > or = 18 years who answered "yes" or "no" to the following question: "Have you ever been told by a doctor, nurse, or other health professional that you have some form of arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia?" Note that the CDC typically provides this estimate in standard arthritis BRFSS tables produced for each state for odd-numbered years. Unadjusted data are usually presented in these tables to provide actual estimates to help in state-level program planning | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| BINGE | Binge drinking among adults aged 18+ years | Adults aged > or = 18 years who report having five or more drinks (men) or four or more drinks (women) on an occasion in the past 30 days divided by adults aged > or = 18 years who report having a specific number, including zero, of drinks on an occasion in the past 30 days | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| BPHIGH | High blood pressure among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they have high blood pressure divided by respondents aged > or = 18 years . Women who were told high blood pressure only during pregnancy and those who were told they had borderline hypertension were not included | Cross-sectional | Census tract | 2015 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| BPMED | Taking medicine for high blood pressure control among adults aged 18+ years with high blood pressure | Respondents aged > or = 18 years who report taking medicine for high blood pressure divided by respondents aged > or = 18 years who report having been told by a doctor, nurse, or other health professional of having high blood pressure other than during pregnancy | Cross-sectional | Census tract | 2015 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CANCER | Cancer (excluding skin cancer) among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they have any other types (besides skin) of cancer divided by respondents aged > or = 18 years | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CASTHMA | Current asthma prevalence among adults aged 18+ years | Weighted number of respondents who answer "yes" both to both of the following questions: "Have you ever been told by a doctor, nurse, or other health professional that you have asthma?" and the question "Do you still have asthma?" divided by weighted number of respondents to BRFSS (or National Survey of Children’s Health) excluding "don’t know" and "refused" responses to the question "Have you ever been told you have asthma?" | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CHD | Coronary heart disease among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they had angina or coronary heart disease divided by Respondents aged > or = 18 years who report or do not report ever having been told by a doctor, nurse, or other health professional that they had angina or coronary heart disease | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CHECKUP | Visits to doctor for routine checkup within the past year among adults aged 18+ years | Respondents aged > or = 18 years who report having been to a doctor for a routine checkup (e.g., a general physical exam, not an exam for a specific injury, illness, condition) in the previous year divided by respondents aged > or = 18 years who report or do not report having been to a doctor for a routine checkup in the previous year | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CHOLSCREEN | Cholesterol screening among adults aged 18+ years | Respondents aged > or = 18 years who report having their cholesterol checked within the previous 5 years divided by respondents aged > or = 18 years | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| COLON_SCREEN | Fecal occult blood test, sigmoi- doscopy, or colonoscopy among adults aged 50–75 years | Respondents aged 50–75 years who report having had 1) a fecal occult blood test (FOBT) within the past year, 2) a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or 3) a colonoscopy within the past 10 years divided by respondents aged 50–75 years who report ever having or never having an FOBT, sigmoidoscopy, or colonoscopy | Cross-sectional | Census tract | 2015 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| COPD | Chronic obstructive pulmonary disease among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they had chronic obstructive pulmonary disease (COPD), emphysema, or chronic bronchitis divided by respondents aged > or = 18 years who report or do not report ever having been told by a health professional that they had COPD, emphysema, or chronic bronchitis | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| COREM | Older adult men aged 65+ years who are up to date on a core set of clinical preventive services by age and sex | Number of men aged > or = 65 years reporting having received all of the following: an influenza vaccination in the past year; a PPV ever; and either a fecal occult blood test (FOBT) within the past year, a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or a colonoscopy within the past 10 years divided by Number of men aged > or = 65 years | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| COREW | Older adult women aged 65+ years who are up to date on a core set of clinical preventive services by age and sex | Number of women aged > or = 65 years reporting having received all of the following: an influenza vaccination in the past year; a pneumococcal vaccination (PPV) ever; either a fecal occult blood test (FOBT) within the past year, a sigmoidoscopy within the past 5 years and a FOBT within the past 3 years, or a colonoscopy within the previous 10 years; and a mammogram in the past 2 years divided by number of women aged > or = 65 years | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| CSMOKING | Current smoking among adults aged 18+ years | Respondents aged > or = 18 years who report having smoked > or = 100 cigarettes in their lifetime and currently smoke every day or some days divided by respondents aged > or = 18 years who reported information about cigarette smoking | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| DENTAL | Visits to dentist or dental clinic among adults aged 18+ years | Respondents aged > or = 18 years who report having been to the dentist or dental clinic in the previous year divided by Respondents aged > or = 18 years (exclude unknowns and refusals) | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| DIABETES | Diagnosed diabetes among adults aged 18+ years | Respondents aged > or = 18 years who report ever been told by a doctor, nurse, or other health professional that they have diabetes other than diabetes during pregnancy divided by respondents aged > or = 18 years who report or do not report ever been told by a health professional that they have diabetes | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| HIGHCHOL | High cholesterol among adults aged 18+ years | Respondents aged > or = 18 years who report having been told by a doctor, nurse, or other health professional that they had high cholesterol divided by respondents aged > or = 18 years who report having their cholesterol checked within the past 5 years | Cross-sectional | Census tract | 2015 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| KIDNEY | Chronic kidney disease among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they have kidney disease divided by respondents aged > or = 18 years who report or do not report ever having been told by a doctor, nurse, or other health professional that they have kidney disease | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| LPA | No leisure-time physical activity among adults aged 18+ years | Respondents who answered "no" to the following question: "During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?" divided by number of adults aged > or = 18 years who reported any or no physical activity in the past month | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| MAMMOUSE | Mammography use among women aged 50-74 years | Female respondents aged 50–74 years who report having had a mammogram within the previous 2 years divided by female respondents aged 50–74 years who report ever having or never having had a mammogram (excluding unknowns and refusals) | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| MHLTH | Mental health not good for 14+ days among adults aged 18+ years | Respondents aged > or = 18 years who report 14 or more days during the past 30 days during which their mental health was not good divided by respondents aged > or = 18 years who report or do not report the number of days during the past 30 days during which their mental health was not good | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| OBESITY | Obesity among adults aged 18+ years | Respondents aged > or = 18 years who have a body mass index (BMI) > or = 30.0 kg/m2 calculated from self-reported weight and height divided by respondents aged > or = 18 years for whom BMI can be calculated from their self-reported weight and height. The following exclusions apply: Height - data from respondents measuring or = 8 ft, Weight - data from respondents weighing or = 650 lbs, BMI - data from respondents with BMI or = 100 kg/m2, and Pregnant women | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| PAPTEST | Pap smear use among adult women aged 21-65 years | Female respondents aged 21–65 years who do not report having had a hysterectomy and who report having had a Papanicolaou (Pap) smear within the previous 3 years divided by female respondents aged 21–65 years who do not report having had a hysterectomy and who report ever having or never having had a Pap smear | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| PHLTH | Physical health not good for 14+ days among adults aged 18+ years | Respondents aged > or = 18 years who report 14 or more days during the past 30 days during which their physical health was not good divided by respondents aged > or = 18 years who report or do not report the number of days during the past 30 days during which their physical health was not good | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| SLEEP | Sleeping less than 7 hours among adults aged 18+ years | Respondents aged > or = 18 years who report usually getting insufficient sleep ( or = 18 years who report 0–24 hours of sleep | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| STROKE | Stroke among adults aged 18+ years | Respondents aged > or = 18 years who report ever having been told by a doctor, nurse, or other health professional that they have had a stroke divided by Respondents aged > or = 18 years who report or do not report ever having been told by a doctor, nurse, or other health professional that they have had a stroke | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| TEETHLOST | All teeth lost among adults aged 65+ years | Respondents aged > or = 65 years who report having lost all of their natural teeth because of tooth decay or gum disease divided by Respondents aged > or = 65 years | Cross-sectional | Census tract | 2016 | <1 | 500 Cities | tract_health_and_ins_stats | Note the naming conventions by this example column name: MHLTH_16_ucl. The first section is the variable name, MHLTH, followed by either a 15 or 16 denoting the year, and then a second optional post-fix noting the value as the upper confidence limit (_ucl) or lower confidence limit (_lcl) of that year's measure. |
| PTGNRL | General election participation | Percent of active voters participating in general elections | Cross-sectional | Block group | 2012 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTPRIM | Primary election participation | Percent of active voter participating in primary elections | Cross-sectional | Block group | 2012 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTASNL | Asian | The percent of the total population reporting their race to be Asian and ethnicity as not Latino or Hispanic. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTBLKNL | Black/African American | The percent of the total population reporting their race to be Black or African American and ethnicity as not Latino or group Hispanic. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTLAT | Hispanic/Latino | The percent of the total population reporting their ethnicity to be Latino or Hispanic. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTWHNL | White | The percent of the total population reporting their race to be White and ethnicity as not Latino or Hispanic. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTOTHNL | Other race | The percent of the total population reporting their race to be American Indian, Hawaiian and Pacific Islander, Other Race, Two or More Races and their ethnicity as not Latino or Hispanic. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| MEDAGE | Median age | The age at the midpoint of the population. Half of the population is older than this age, and half is younger. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| POPDENS | Population density | This measurement provides the population per square mile based on the 2010 Census using blockgroups. | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| REDIV | Race/ethnic diversity | The calculation of this measurement uses the Simpson Index of Diversity, which measures the variety and evenness of different groups. The component numbers for this measure are blockgroup counts of White (not Hispanic), Black or African American (not Hispanic), Asian (not Hispanic), Hispanic or Latino/a, Two or More Races (not Hispanic), and Other (not Hispanic). A higher number in this measure reflects both a higher number of race/ethnicity categories present and more people of each identity present. A diversity measurement of 1 would mean all race and ethnicity identities are present and equally represented, while a measure of 0 would indicate only one race or ethnicity is present. | Cross-sectional | Block group | 2010 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PT65UP | Retirement-age population | The percent of population 65 years of age and older is calculated using the same Decennial Census counts of population as those used for total population, population density, and race and ethnicity. The population 65 years and older is divided by the total population for each blockgroup. | Cross-sectional | Block group | 2010 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PTUND18 | Youth population | The percent of population under 18 years of age is calculated using the same Decennial Census counts of population as those used for total population, population density, and race and ethnicity. The population under 18 years of age is divided by the total population for each blockgroup. | Cross-sectional | Block group | 2010 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| MEANRPMT | Average residential building permit value | The average value of residential building permits for each boundary. These permits include new construction as well as renovations and exclude demolitions. As with the value of permits when normalized by square miles, the average permit values shown here are skewed strongly toward areas of Durham that see substantial private investment in apartment building construction. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 6 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CPMTS | Commercial building permit value per sq. mile | The value of commercial, business, and industrial building permits for each boundary divided by the area (in square miles) of each. These permits include new construction as well as renovations and exclude demolitions. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 50 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| COB | Commercial certificates of occupancy per sq. mile | COs included here are the following types: business, mercantile, factory industrial, and mixed use commercial. The count of these per neighborhood or blockgroup is divided by the area in square miles within the City/County Inspections districts. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 50 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| LUDIV | Land use diversity | The calculation of this measurement uses the Simpson Index of Diversity, which measures the variety and evenness of different groups. A higher number in this measure reflects both a higher number of land use types in each area and a more balanced number of properties among them. Parcels are categorized as: agricultural, residential, commercial, recreation, industrial, community services, public services (utilities), wild and forested lands. A measure of 1 would mean each of the possible types of land use is present and that there is an equal number of each. A measure of 0 would mean only one type is present. | Cross-sectional | Block group | 2013 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| MEDINC | Median household income | The household income at the midpoint of all households. Half of the households in this Census tract earn a higher annual income and half earn a lower annual income. These amounts are inflation-adjusted for 2010 using the Consumer Price Index for all items, referencing the South urban areas (table CUUR0300SA0). | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCI | Per capita income | Average obtained by dividing aggregate income by total population of an area. These amounts are inflation-adjusted for 2011. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| RPMTS | Residential building permit value per sq. mile | The value of residential building permits for each boundary divided by the area (in square miles) of each. These permits include new construction as well as renovations and exclude demolitions. Even when normalized by square miles, as these numbers are, strong outliers skew the data. Some areas of Durham receive tremendous amounts of housing investment as private apartment development continues near downtown. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 6 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| COR | Residential certificates of occupancy per sq. mile | COs included here are the following types: residential, single family, townhouse, condominium, duplex, manufactured homes, and mixed-use residential. The count of these per neighborhood or blockgroup is divided by the area in square miles within the City/County Inspections districts. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 5 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCTSSI | Supplemental Social Security income | Time series | Census tract | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. | |
| CCC | Child care centers per sq. mile | This measure includes both child care centers and family child care homes which are licensed by the state of North Carolina's Division of Child Care and Early Development. It does not include unlicensed locations. Data is collected each year in April and reflects a snapshot of the calendar year's licensed centers. | Time series | Block group | 2013, 2014, 2015, 2016, 2017, 2018 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CC45 | Child care centers with 4 or 5 star rating | This measure includes both child care centers and family child care homes which are licensed by the state of North Carolina's Division of Child Care and Early Development. It does not include unlicensed locations. Data is collected each year in April and reflects a snapshot of the calendar year’s licensed centers. | Time series | Block group | 2013, 2014, 2015, 2016, 2017, 2018 | 25 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| BACH | Percent adults with bachelor's degree or more | Along with other tract data from US 2010 included here, this measure is derived from 1970-2010 US Census Bureau surveys for 2010-normalized Census tract boundaries. | Cross-sectional | Census tract | 2010 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| VCODE | Automotive code violations | The number of automotive code violations divided by the square miles of each blockgroup that lie within the City boundary. This measurement includes abandoned and hazardous, as well as junked vehicle violations. It excludes calls found to be not in violation. This measurement reflects a City-only service and parts of Durham County are not represented by this data. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 3.8 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| KWH | Avg. monthly household electricity use | This data is derived from household energy use for Duke Energy customers throughout Durham County for the years 2013-2014. Household use is averaged for each bockgroup for each month of the calendar year and then averaged across the year as well. The numbers reported here are calendar year averages. | Cross-sectional | Block group | 2013, 2014 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCTIMP | Impervious area | This measurement is derived from 2009-2011 National Agricultural Imagery Program one-meter digital photography for the EPA EnviroAtlas, and reports only on the urbanized area of Durham County. It represents the percent of total land within each block group that is impervious and not covered by tree canopy. | Cross-sectional | Block group | 2011 | 11 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCTC30 | Long commute times | This data includes all those commuting to the workplace, whether in personal vehicles, bicycles, walking or by public transit. As of 2010, the Durham County mean commuting time was 21.7 minutes. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DRALONE | Single-occupancy commuters | This data indicates the percentage of surveyed residents who commute by driving a personal vehicle such as a car, truck or van with no additional passengers. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCTTREE | Tree coverage | This measurement is derived from 2009-2011 National Agricultural Imagery Program one-meter digital photography for the EPA EnviroAtlas, and reports only on the urbanized area of Durham County. It represents the percent of total land cover within each block group that is tree canopy, whether in forests, along streets, or individual trees. | Cross-sectional | Block group | 2011 | 11 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| WCODE | Unmaintained property violations per sq. mile | The number of unmaintained property violations divided by the square miles of each blockgroup that lie within the City boundary. This measurement includes all unmaintained property (weedy lot) violations, not including calls found to be not in violation or those involving commercial properties. This measurement, along with residential building code violations and abandoned, hazardous or junked vehicles reflect a City-only service and parts of Durham County are not represented by this data. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 3.8 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| AVEAGE | Average age of death | The average age of death here is reported for 2009 (reflecting records from 2005-2009) and 2014 (reflecting records from 2010-2014). | Time series | Block group | 2010, 2011, 2012, 2013, 2014 | 4.5 | DataWorks NC | tract_dataworks_county_and_census_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_TOTAL | Chronic kidney disease rate | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_ASIAN | Chronic kidney disease Asian | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | 10 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_BLACK | Chronic kidney disease Black | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_FEMALE | Chronic kidney disease female | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_HISPANIC | Chronic kidney disease Hispanic | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_MALE | Chronic kidney disease male | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CKD_WHITE | Chronic kidney disease white | These chronic kidney disease rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Rates selected for inclusion in this site are those matching CDC guidelines as reported by Duke Health. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_TOTAL | Diabetes rate | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_ASIAN | Diabetes rate Asian | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | 10 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_BLACK | Diabetes rate Black | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_FEMALE | Diabetes rate female | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_HISPANIC | Diabetes rate Hispanic | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_MALE | Diabetes rate male | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| DIABETES_WHITE | Diabetes rate white | These type 2 diabetes rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HEARTATTACK_TOTAL | Heart attack rate | Heart attack or MI diagnoses are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Heart attack or MI incidents are those coded as ICD 410.01, 410.11, 410.21, 410.31, 410.41, 410.51, 410.61, 410.71, 410.81, 410.91, I21, I22 and I25.2. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HEARTATTACK_BLACK | Heart attack rate Black | Heart attack or MI diagnoses are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Heart attack or MI incidents are those coded as ICD 410.01, 410.11, 410.21, 410.31, 410.41, 410.51, 410.61, 410.71, 410.81, 410.91, I21, I22 and I25.2. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HEARTATTACK_FEMALE | Heart attack rate female | Heart attack or MI diagnoses are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Heart attack or MI incidents are those coded as ICD 410.01, 410.11, 410.21, 410.31, 410.41, 410.51, 410.61, 410.71, 410.81, 410.91, I21, I22 and I25.2. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HEARTATTACK_MALE | Heart attack rate male | Heart attack or MI diagnoses are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Heart attack or MI incidents are those coded as ICD 410.01, 410.11, 410.21, 410.31, 410.41, 410.51, 410.61, 410.71, 410.81, 410.91, I21, I22 and I25.2. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HEARTATTACK_WHITE | Heart attack rate white | Heart attack or MI diagnoses are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). Heart attack or MI incidents are those coded as ICD 410.01, 410.11, 410.21, 410.31, 410.41, 410.51, 410.61, 410.71, 410.81, 410.91, I21, I22 and I25.2. | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| STROKE_TOTAL | Stroke rate | These stroke rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| STROKE_BLACK | Stroke rate Black | These stroke rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| STROKE_FEMALE | Stroke rate female | These stroke rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| STROKE_MALE | Stroke rate male | These stroke rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| STROKE_WHITE | Stroke rate white | These stroke rates are based on health care visits documented in this combined dataset, including a total of 169,115 adults of a countywide total of 245,572 (2017). | Cross-sectional | Census tract | 2015, 2017 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| CLINIC | Homes near health care clinics | Clinic locations are current as of May 2018 and sourced from the Durham County Social Services Department, Lincoln Community Health and Duke Division of Community Health. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of health clinics by the total number of dwelling units in the blockgroup. | Cross-sectional | Block group | 2018 | <1 | DataWorks NC | tract_health_and_ins_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| RAVGYR | Avg. year of residential construction | The average age of all residential units - including single-family, multi-family, townhouse and all other residential categories. | Time series | Block group | 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| UNFOWN | Cost-burdened mortgage holders | This includes selected monthly ownership costs such as mortgage or similar debts, taxes, insurance, utilities, and condo or group homeowners fees. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | 4 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| UNFRENT | Cost-burdened renters | Gross rent as a percentage of household income is a computed ratio of monthly gross rent to monthly household income. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | 2 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| MEDGRENT | Median gross rent | The median gross rent is at the midpoint of all rent costs for each neighborhood. Half of the rental units in this Census tract cost more and half cost less. Gross rent includes the contract rent plus estimated monthly costs of utilities and heating fuels if these are paid for by the renter (ACS). | Time series | Block group | 2010, 2011, 2012, 2013, 2014, 2015, 2016 | 3 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| MEDHV | Median home value | The home value at the midpoint of all home values. Half of the homes in this Census tract are valued higher and half valued lower. These amounts are inflation-adjusted for 2010 using the Consumer Price Index for all items, referencing the South urban areas (table CUUR0300SA0). | Cross-sectional | Census tract | 2010 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| HMINC | Median home-buyer income | Dollar values are adjusted to most-recent-year dollars to offer a real comparison in household wealth. Records included in this analysis are for origninated, owner-occupant mortgages only. | Time series | Census tract | 2012, 2013, 2014, 2015, 2016, 2017 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| RCODE | Minimum housing code violations per sq. mile | The number of minimum housing code violations divided by the square miles of each blockgroup that lie within the City boundary. This measurement includes all minimum housing code violations, excluding calls found to be not in violation. This does include orders to repair, demolish, unsafe structures, and boarded properties. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017 | 4 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PRUNSD | Poor or unsound state of repair | State of repair for all properties is reported in 5 categories in the Tax Administration’s property records. The five categories are good, normal, fair, poor, and unsound. The latter two are defined as follows: poor, showing marked deterioriation; unsound, may be unfit for habitation or condemned. For the measure reported here, these two categories are combined. | Time series | Block group | 2013, 2014, 2015 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PCTRENT | Renter-occupied housing | All occupied units which are not owner occupied, whether they are rented for cash rent or occupied without payment of cash rent, are classified as renter-occupied. Renter-occupied status also applies to units in continuing care arrangements, such as assisted living. | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| SUMEJECT | Summary ejections per sq. mile | DataWorks acquires civil process records from the Durham County Sheriff’s Department for use at the neighborhood level. These are records of the Sheriff’s Department notifications to tenants and do not include any personally-identifiable information. The number of these summary ejectment filings per Census blockgroup is divided by the area of the blockgroup in square miles.NOTE: Summary ejectment counts published here are revised as of May 17, 2019. These counts represent a modest increase across the county per year with the largest change (an additional 203 summary ejectments) in 2013. Among the blockgroups of the county, these new counts vary from previous summaries published here, with 81% of blockgroups seeing less than a 10-count change in any given year. These Compass summaries are now managed within our databases to ensure future stability in counts and reproducibility. To learn more about this change and how we manage evictions data contact tech@dataworks-nc.org. | Time series | Block group | 2012, 2013, 2014, 2015, 2016, 2017, 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| REVAL | Tax value change | This rate of change is derived from parcel point data from 2014 (previous to the most recent property tax revaluation) and 2016. 2015 records were not used for the before-and-after comparison because many but not all records for 2015 parcels already included revalued estimates and the appeal process had not yet begun. The number reported here is a median rate of change for every property in a blockgroup. Properties with zero value in 2014 or zero values in both years were excluded from this calculation to prevent skewing by outliers. | Cross-sectional | Block group | 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| BIKEWK | Percent commuting to work by bike | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. | |
| PROXBANK | Homes near banks/credit unions | This measurement includes both commercial bank locations and credit unions. These are identified primarily by North American Industry Classification System (NAICS) codes 52211 and 52213 and then conducting a qualitative scan of additional community businesses. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of banks or credit unions by the total number of dwelling units in the blockgroup. Which blockgroup a parcel belongs to is determined by where its centroid is placed. | Cross-sectional | Block group | 2014, 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PROXBUS | Homes near bus stops | Households include all residential units, not just residential parcels. Bus stop locations used in this calculation are those active during the spring of each calendar year. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of bus stops by the total number of dwelling units in the blockgroup. Which blockgroup a parcel belongs to is determined by where its centroid is placed. | Time series | Block group | 2013, 2014, 2015, 2016, 2017, 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PROXCF | Homes near fast food/convenience stores | Fast food and convenience store locations include fast food chains, gas station/convenience stores, dollar stores and pizza places. These are identified first by using North American Industry Classification System (NAICS) codes for convenience stores and fast food in the InfoUSA data set and then conducting a qualitative scan of additional community businesses. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of these food retailers by the total number of dwelling units in the blockgroup. Which blockgroup a parcel belongs to is determined by where its centroid is placed. | Cross-sectional | Block group | 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PROXGR | Homes near grocery stores | Full service grocers include chain grocery stores and independent full-service stores but do not include farmers’ markets. Full service grocers are identified primarily by North American Industry Classification System (NAICS) code 44511 and then conducting a qualitative scan of additional community businesses. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of grocers by the total number of dwelling units in the blockgroup. Which blockgroup a parcel belongs to is determined by where its centroid is placed. | Cross-sectional | Block group | 2013, 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| PROXPH | Homes near pharmacies | Pharmacies include traditional storefront locations of independent and chain drug stores, as well as big-box retail locations. These are identified primarily by North American Industry Classification System (NAICS) code 44611 and then conducting a qualitative scan of additional community businesses. Households are identified in this case as parcels with dwelling units and the 1/4 mile distance is Euclidean, or as-the-crow-flies. The rate is calculated by dividing the number of dwelling units within a 1/4 mile of pharmacies by the total number of dwelling units in the blockgroup. Which blockgroup a parcel belongs to is determined by where its centroid is placed. | Cross-sectional | Block group | 2014, 2018 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| SWTORD | Sidewalks to roadways | The intention of this measurement is to indicate how well neighborhood roads serve pedestrians. Pedestrian or bike paths not adjacent to roadways are not among the sidewalks counted here. Areas reporting 'N/A' are outside City limits and do not contain annexed communities - the City does not maintain or build sidewalks in those areas. | Time series | Block group | 2013, 2014, 2015, 2016 | 4.3 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| WLKWK | Percent walking to work | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. | |
| WKHOME | Percent working from home | Time series | Block group | 2011, 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. | |
| D_SQM | Drug crimes per sq. mile | Drug-related crimes include all incidents involving drug and paraphernalia manufacturing, distributing, and possession charges. For more detailed Durham crime reporting visit RAIDS Online. | Time series | Block group | 2012, 2013, 2014, 2015, 2016 | 11 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| P_SQM | Property crimes per sq. mile | Property crimes are commonly reported with parts 1 and 2 separate. This measurement is different, including all part 1 property crimes and these part 2 crimes: fraud, forgery, embezzlement, counterfeiting, stolen property and vandalism. The number of property crimes occurring in each boundary is divided by the area (in square miles) of the boundary, rather than the population. This is intended to control for how crime often happens in areas that are less populated. For more detailed Durham crime reporting visit RAIDS Online. | Time series | Block group | 2012, 2013, 2014, 2015, 2016 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| V_SQM | Violent crimes per sq. mile | Violent crimes are commonly reported with parts 1 and 2 separate. This measurement is different, including all part 1 violent crimes and these part 2 crimes: simple assaults, certain sex offenses, child abuse and kidnapping. The number of these violent crimes occurring in each boundary is divided by the area (in square miles) of the boundary, rather than the population. This is intended to control for how crime often happens in areas that are less populated. For more detailed Durham crime reporting visit RAIDS Online. | Cross-sectional | Block group | 2012 | <1 | DataWorks NC | tract_misc_housing_work_and_crime_stats | Note the naming conventions by this example column name: MEDINC_11_moe. The first section is the variable name, MEDINC, followed by a number denoting the year, and then a second optional post-fix noting the value as the margin of error (_moe) of that year's measure. |
| rac_TotNum_Jobs | Total number of jobs | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_<29 | Number of jobs for workers age 29 or younger | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_30-54 | Number of jobs for workers age 30 to 54 | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_55+ | Number of jobs for workers age 55 or older | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_<1250 | Number of jobs with earnings $1250/month or less | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_1251-3333 | Number of jobs with earnings $1251/month to $3333/month | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_3333+ | Number of jobs with earnings greater than $3333/month | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_AFFH | Number of jobs in NAICS sector 11 (Agriculture, Forestry, Fishing, and Hunting) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_MQOG | Number of jobs in NAICS sector 21 (Mining, Quarrying, and Oil and Gas Extraction) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Util | Number of jobs in NAICS sector 22 (Utilities) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Const | Number of jobs in NAICS sector 23 (Construction) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Manuf | Number of jobs in NAICS sector 31-33 (Manufacturing) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_WSale | Number of jobs in NAICS sector 42 (Wholesale Trade) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_RSale | Number of jobs in NAICS sector 44-45 (Retail Trade) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_TrWa | Number of jobs in NAICS sector 48-49 (Transportation and Warehousing) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Info | Number of jobs in NAICS sector 51 (Information) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_FinIns | Number of jobs in NAICS sector 52 (Finance and Insurance) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_RERL | Number of jobs in NAICS sector 53 (Real Estate and Rental and Leasing) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_PSTS | Number of jobs in NAICS sector 54 (Professional, Scientific, and Technical Services) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Mgmt | Number of jobs in NAICS sector 55 (Management of Companies and Enterprises) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_ASWSR | Number of jobs in NAICS sector 56 (Administrative and Support and Waste Management and Remediation Services) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Edu | Number of jobs in NAICS sector 61 (Educational Services) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_HlthSA | Number of jobs in NAICS sector 62 (Health Care and Social Assistance) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_AER | Number of jobs in NAICS sector 71 (Arts, Entertainment, and Number Census _AER Recreation) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_AFS | Number of jobs in NAICS sector 72 (Accommodation and Food Services) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Other | Number of jobs in NAICS sector 81 (Other Services [except Public Administration]) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_PA | Number of jobs in NAICS sector 92 (Public Administration) | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_White | Number of jobs for workers with Race: White, Alone | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_BAA | Number of jobs for workers with Race: Black or African American Alone | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_AIAN | Number of jobs for workers with Race: American Indian or Alaska Native Alone | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Asian | Number of jobs for workers with Race: Asian Alone | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_NHPA | Number of jobs for workers with Race: Native Hawaiian or Other Pacific Islander | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Two | Number of jobs for workers with Race: Two or More Race Groups | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_NotHL | Number of jobs for workers with Ethnicity: Not Hispanic or Latino | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_HL | Number of jobs for workers with Ethnicity: Hispanic or Latino | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_<HS | Number of jobs for workers with Educational Attainment: Less than high school | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_HS | Number of jobs for workers with Educational Attainment: High school or equivalent | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_SomeCollege | Number of jobs for workers with Educational Attainment: Some college or Associate | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_BachDegree+ | Number of jobs for workers with Educational Attainment: Bachelor’s degree or advanced degree | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Male | Number of jobs for workers with Sex: Male | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| rac_NumJobs_Female | Number of jobs for workers with Sex: Female | Time series | Census tract | 2002-2015 | all years <1, except 2003 (2.4), 2012 (5), 2014 (4.9), 2015 (1.1) | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Resident Area Characteristics | tract_rac_job_stats | Note the naming conventions by this example column name: rac_NumJobs_<1250_02. The first section is the variable name, rac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_TotNum_Jobs | Total number of jobs | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_<29 | Number of jobs for workers age 29 or younger | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_30-54 | Number of jobs for workers age 30 to 54 | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_55+ | Number of jobs for workers age 55 or older | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_<1250 | Number of jobs with earnings $1250/month or less | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_1251-3333 | Number of jobs with earnings $1251/month to $3333/month | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_3333+ | Number of jobs with earnings greater than $3333/month | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_AFFH | Number of jobs in NAICS sector 11 (Agriculture, Forestry, Fishing, and Hunting) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_MQOG | Number of jobs in NAICS sector 21 (Mining, Quarrying, and Oil and Gas Extraction) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Util | Number of jobs in NAICS sector 22 (Utilities) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Const | Number of jobs in NAICS sector 23 (Construction) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Manuf | Number of jobs in NAICS sector 31-33 (Manufacturing) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_WSale | Number of jobs in NAICS sector 42 (Wholesale Trade) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_RSale | Number of jobs in NAICS sector 44-45 (Retail Trade) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_TrWa | Number of jobs in NAICS sector 48-49 (Transportation and Warehousing) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Info | Number of jobs in NAICS sector 51 (Information) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FinIns | Number of jobs in NAICS sector 52 (Finance and Insurance) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_RERL | Number of jobs in NAICS sector 53 (Real Estate and Rental and Leasing) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_PSTS | Number of jobs in NAICS sector 54 (Professional, Scientific, and Technical Services) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Mgmt | Number of jobs in NAICS sector 55 (Management of Companies and Enterprises) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_ASWSR | Number of jobs in NAICS sector 56 (Administrative and Support and Waste Management and Remediation Services) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Edu | Number of jobs in NAICS sector 61 (Educational Services) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_HlthSA | Number of jobs in NAICS sector 62 (Health Care and Social Assistance) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_AER | Number of jobs in NAICS sector 71 (Arts, Entertainment, and Number Census _AER Recreation) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_AFS | Number of jobs in NAICS sector 72 (Accommodation and Food Services) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Other | Number of jobs in NAICS sector 81 (Other Services [except Public Administration]) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_PA | Number of jobs in NAICS sector 92 (Public Administration) | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_White | Number of jobs for workers with Race: White, Alone | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_BAA | Number of jobs for workers with Race: Black or African American Alone | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_AIAN | Number of jobs for workers with Race: American Indian or Alaska Native Alone | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Asian | Number of jobs for workers with Race: Asian Alone | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_NHPA | Number of jobs for workers with Race: Native Hawaiian or Other Pacific Islander | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Two | Number of jobs for workers with Race: Two or More Race Groups | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_NotHL | Number of jobs for workers with Ethnicity: Not Hispanic or Latino | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_HL | Number of jobs for workers with Ethnicity: Hispanic or Latino | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_<HS | Number of jobs for workers with Educational Attainment: Less than high school | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_HS | Number of jobs for workers with Educational Attainment: High school or equivalent | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_SomeCollege | Number of jobs for workers with Educational Attainment: Some college or Associate | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_BachDegree+ | Number of jobs for workers with Educational Attainment: Bachelor’s degree or advanced degree | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Male | Number of jobs for workers with Sex: Male | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_Female | Number of jobs for workers with Sex: Female | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmAge_<1 | Number of jobs for workers at firms with Firm Age: 0-1 Years | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmAge_2-3 | Number of jobs for workers at firms with Firm Age: 2-3 Years | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmAge_4-5 | Number of jobs for workers at firms with Firm Age: 4-5 Years | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmAge_6-10 | Number of jobs for workers at firms with Firm Age: 6-10 Years | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmAge_11+ | Number of jobs for workers at firms with Firm Age: 11+ Years | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmSize_<19 | Number of jobs for workers at firms with Firm Size: 0-19 Employees | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmSize_20-49 | Number of jobs for workers at firms with Firm Size: 20-49 Employees | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmSize_50-249 | Number of jobs for workers at firms with Firm Size: 50-249 Employees | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmSize_250-499 | Number of jobs for workers at firms with Firm Size: 250-499 Employees | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. | |
| wac_NumJobs_FirmSize_500+ | Number of jobs for workers at firms with Firm Size: 500+ Employees | Time series | Census tract | 2002-2015 | <1 | Longitudinal Employer-Household Dynamics Origin-Destination Employment Statistics, Worksplace Area Characteristics | tract_wac_job_stats | Note the naming conventions by this example column name: wac_NumJobs_<1250_02. The first section is the variable name, wac_NumJobs, followed by a 2-digit number denoting the year. |
