Gary Hart, PhD Director & Professor Center for Rural Health School of Medicine and Health Sciences University of North Dakota Grand Forks, North Dakota Fron@er Partners Mee@ng March 27, 2012 Note: Parts of this material are taken from Dr. John Cromar4e s presenta4ons but Dr. Hart is responsible for errors.
Core Inves@gators Ø John Cromar*e (ERS) Ø Gary Hart (U of ND) Ø Project Officer of ORHP Funding: Steve Hirsch
Fron@er and Remote (FAR) Codes (na4onal fron4er area taxonomy) Gary Hart, PhD Director & Professor Center for Rural Health School of Medicine and Health Sciences University of North Dakota Grand Forks, North Dakota John Cromar*e, PhD Geographer Economic Research Service Department of Agriculture Washington, District of Columbia David Nulph Systems Analyst Economic Research Service Department of Agriculture Washington, District of Columbia Funded by HRSA s Office of Rural Health Policy & USDA s Economic Research Service
Fron@er/Remote Defini@on Project Funding Ø HRSA s Office of Rural Health Policy Ø USDA s Economic Research Service
Why Fron*er? ORHP has focused resources on how best to define rural There is no formal statutory defini*on of a fron*er area Current defini*ons of rural do not adequately delineate those areas that are truly remote and isolated Steve Hirsch
Why Identify Frontier Areas? Target populations which will likely require public intervention to assure a core set of health services. Public Purposes: Assure the geographic equity of the health service system. Establish a standby capacity of key services where low volume makes market solutions unlikely. Harvey Licht, NM SORH
Project Objec@ves Ø Produce a na*onal Fron*er/Remote defini*on Ø Obtain stakeholder input Ø Review literature Ø U*lize leading experts and rigorous inves*ga*ons Ø Create na*onal defini*on (not just health care) acceptable to ORHP and ERS Ø If defini*on does not work for islands, create a separate defini*on for them Ø Disseminate the defini*on and update it at regular intervals
Project Objec@ves Ø Two- Year Project Ø Core Inves*gators Ø Internal Technical Group Ø Internal Stakeholder Group Ø Stakeholder Input Mee*ngs Ø Tes*ng & Implementa*on Alterna*ves Ø Selec*on of Defini*on Ø Feedback on Penul*mate Ø Descrip*on and Dissemina*on (& subsequent updates)
Project Objec@ves Ø Two- Year Project Ø Core Inves*gators Ø Internal Technical Group Ø Internal Stakeholder Group Ø Stakeholder Input Mee*ngs Ø Tes*ng & Implementa*on Alterna*ves Ø Selec*on of Defini*on Ø Feedback on Penul*mate Ø Descrip*on and Dissemina*on (& subsequent updates)
Penul4mate Dra> Project Version 2.99 Selected Fron@er/Remote, Island, and Rural Literature Review Gary Hart, PhD Director & Professor Center for Rural Health School of Medicine and Health Sciences University of North Dakota Grand Forks, North Dakota John Cromar*e, PhD Geographer Economic Research Service Department of Agriculture Washington, District of Columbia Funded by HRSA s Office of Rural Health Policy & USDA s Economic Research Service August 12, 2012 (Version 2.99 Drad (B53))
Regional Mee@ng Summary #1 Ø Discussions were broad good ideas Ø Keep mul* purposes in mind Ø Overall Agreement: Ø Objec*ve, reliable, prac*cal reproducible, straighjorward Ø Uses key data sources Ø Independent of program objec*ves but policy relevant
Regional Mee@ng Summary #2 Ø A defini*on not THE defini*on Ø Word Fron*er issues Ø Too many defini*ons? Ø Isola*on versus remoteness Ø Strictly physical measures
Regional Mee@ng Summary #3 Ø Favor sub county defini*on Ø Flexibility in taxonomy with mul*ple categories and implementa*on Ø Ability to implement with screens of addi*onal informa*on (e.g., poverty, poor access to primary care, etc.)
Innova@ve New Methods Ø Na*on in 1 kilometer squares (about 10 football fields) (11.9 million) Ø Popula*on Ø Travel *mes to various Census Bureau defined urban places/clusters (e.g., 2.5K, 10K, 25K) and urbanized areas (e.g., 50K and greater) Ø Aggregate to residen*al ZIP code areas, Census tracts, etc.
Why use the term fron*er? Fron*er delinea*on is mostly about remoteness but also has elements of popula*on size and density, so remote areas is a limle misleading History of mul*ple, overlapping, evolving, some*mes opposing meanings; adap*on here seems a natural progression French military term for bamle lines à different types of border areas dividing the known and unknown (poli*cal, cultural) à line of European conquest and semlement in America and elsewhere à the region beyond the line Census Bureau, Frederick Jackson Turner, and Turner s cri*cs made it an essen*ally regional, demographic concept
There are 400 coun@es with density under 6.01 people per sq. mile.
Why define fron*er areas for ERS? Remoteness bestows highly- cherished benefits, but also economic and social challenges. The nega*ve effects of remoteness on job crea*on, popula*on reten*on, and service provision appears to be an inherent feature. ERS priority issues: 1. Explaining popula*on trends fron*er areas are expanding! 2. Return migra*on 3. Aging 4. Food deserts 5. CRP, farm subsidy impacts 6. Health care accessibility The economic penal*es of remoteness may be increasing (Partridge and Rickman, 2008; Partridge et al.; 2008; Partridge et al., 2009). Demand for a fron*er delinea*on that is adjustable within a reasonable range, in order to be usefully applied in different research and policy contexts. Applying longer travel- @me bands around larger ci@es distance effects on popula*on density and other characteris*cs are discon*nuous; on average, the larger the city, the farther from that city one must travel to enter fron*er territory.
Data and Methods Measuring distance using travel *me If the nearest UA is in the 25,000-50,000 size range, then travel *me to UA s in the two lower size ranges is not needed for that grid cell and was not recorded. If the nearest UA has 1 million or more people, then only the travel *me to the edge of that UA is relevant for defining fron*er for that grid cell. For grid cells falling within UA s, travel *mes to higher- level UA s were calculated; for example, for any grid cell in a UA of 2,500-10,000 people, the travel *me to the six higher categories was recorded. No travel *me informa*on was collected for grid cells in ci*es of 1,000,000 or more. 1. 2,500-10,000 2. 10,000-24,999 3. 25,000-49,999 4. 50,000-99,999 5. 100,000-249,999 6. 250,000-999,999 7. 1,000,000 or more Urban Areas in eastern Kansas, 2000 1x1 kilometer grid cell
Isola*on is measured by travel *me to nearby Urban Areas Travel *me bands (minutes from edge of Urban Area): Urban areas 0 30 303 60 90 120
Isola*on is measured by travel *me to nearby Urban Areas Travel *me bands (minutes from edge of Urban Area): Urban areas 0 30 303 60 90 120
FAR Level Defini@ons 1. Level 1: areas are 60 minutes or greater from Census Bureau defined Urban Areas of 50,000 or more popula*on
FAR Level Defini@ons 1. Level 1: areas are 60 minutes or greater from Census Bureau defined Urban Areas of 50,000 or more popula*on 2. Level 2: areas are 60 minutes or greater from Urban Areas of 50,000 or more people and 45 minutes or greater from Urban Areas of 25,000-49,999
FAR Level Defini@ons 1. Level 1: areas are 60 minutes or greater from Census Bureau defined Urban Areas of 50,000 or more popula*on 2. Level 2: areas are 60 minutes or greater from Urban Areas of 50,000 or more people and 45 minutes or greater from Urban Areas of 25,000-49,999 3. Level 3: areas are 60 minutes or greater from Urban Areas of 50,000 or more people; 45 minutes or greater from Urban Areas of 25,000-49,999; and 30 minutes or greater from Urban Areas of 10,000-24,999
FAR Level Defini@ons 1. Level 1: areas are 60 minutes or greater from Census Bureau defined Urban Areas of 50,000 or more popula*on 2. Level 2: areas are 60 minutes or greater from Urban Areas of 50,000 or more people and 45 minutes or greater from Urban Areas of 25,000-49,999 3. Level 3: areas are 60 minutes or greater from Urban Areas of 50,000 or more people; 45 minutes or greater from Urban Areas of 25,000-49,999; and 30 minutes or greater from Urban Areas of 10,000-24,999 4. Level 4: areas are 60 minutes or greater from Urban Areas of 50,000 or more people; 45 minutes or greater from Urban Areas of 25,000-49,999; 30 minutes or greater from Urban Areas of 10,000-24,999; and 15 minutes or greater from Urban Areas of 2,500-9,999
FAR Level Defini@ons 1. Level 1: areas are 60 minutes or greater from Census Bureau defined Urban Areas of 50,000 or more popula*on 2. Level 2: areas are 60 minutes or greater from Urban Areas of 50,000 or more people and 45 minutes or greater from Urban Areas of 25,000-49,999 3. Level 3: areas are 60 minutes or greater from Urban Areas of 50,000 or more people; 45 minutes or greater from Urban Areas of 25,000-49,999; and 30 minutes or greater from Urban Areas of 10,000-24,999 4. Level 4: areas are 60 minutes or greater from Urban Areas of 50,000 or more people; 45 minutes or greater from Urban Areas of 25,000-49,999; 30 minutes or greater from Urban Areas of 10,000-24,999; and 15 minutes or greater from Urban Areas of 2,500-9,999
Cau@on While the FAR popula*on percentages and numbers per the rest of this presenta*on are thought to be correct, they were not checked when transcribed from the computer output to this presenta*on. Thus, cau*on should be exercised in their use un*l final verified sta*s*cs are available. Note: See FAR tables on ERS web site for final numbers per this pilot (hmp://www.ers.usda.gov/data- products/fron*er- and- remote- area- codes.aspx).
% of State Landmass FAR Level 1 (>60 minutes to 50K+) 1. Nevada (90.1%) 2. Montana (87.5%) 3. Nebraska (87.2%) 4. South Dakota (86.8%) 5. Wyoming (86.7%) 6. North Dakota (86.5%) 7. New Mexico (82.2%) 8. Utah (81.8) U.S. (54.8%) Alaska Note: AK & HI not yet included
State Landmass FAR Level 1 (>60 minutes to 50K+) 1. Montana 2. Texas 3. New Mexico 4. Nevada 5. Wyoming 6. Colorado 7. California 8. Arizona 9. Oregon 10. Utah 11. Nebraska 12. South Dakota 13. Kansas 14. North Dakota Note: AK & HI not yet included Alaska
% of State Popula@on FAR by 4 Levels 1. Level 1: 6.5% (18.0 million) 2. Level 2: 4.5% (12.4 million) 3. Level 3: 2.9% ( 8.0 million) 4. Level 4: 1.7% ( 4.8 million) Aggregated to residen@al ZIP code areas ZIPs designated if 50% or more of popula@on qualifies (users will be able to adjust this) Note: Alaska & Hawaii not yet included
% of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Wyoming (61.2%) 2. Montana (57.7%) 3. North Dakota (48.6%) 4. South Dakota (45.4%) 5. Mississippi (39.6%) 6. Nebraska (35.9%) 7. New Mexico (32.4%) 8. Kansas (25.4%) U.S. (6.5%) Note: AK & HI not yet included but AK will make list (around 35% and Hawaii about 25%)
% of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Wyoming (61.2%) 2. Montana (57.7%) 3. North Dakota (48.6%) 4. South Dakota (45.4%) 5. Mississippi (39.6%) 6. Nebraska (35.9%) 7. New Mexico (32.4%) 8. Kansas (25.4%) U.S. (6.5%) F- CHIP States Note: AK & HI not yet included but AK will make list (around 35-40% and Hawaii about 25%)
% of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Wyoming (61.2%) (26) 2. Montana (57.7%) (15) 3. North Dakota (48.6%) (24) 4. South Dakota (45.4%) (20) 5. Mississippi (39.6%) (2) 6. Nebraska (35.9%) (9) 7. New Mexico (32.4%) (11) 8. Kansas (25.4%) (8) U.S. (6.5%) # Popula*on Rank Note: AK & HI not yet included
% of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Wyoming (61.2%) (26) 2. Montana (57.7%) (15) 3. North Dakota (48.6%) (24) 4. South Dakota (45.4%) (20) 5. Mississippi (39.6%) (2) 6. Nebraska (35.9%) (9) 7. New Mexico (32.4%) (11) 8. Kansas (25.4%) (8) U.S. (6.5%) # Popula*on Rank Note: AK & HI not yet included
% of Population Frontier by State FAR Level 1 Definition Wyoming Montana North Dakota South Dakota Mississippi Nebraska New Mexico Kansas Vermont Iowa Kentucky Idaho Arkansas Minnesota West Virginia Oklahoma Missouri Maine Oregon Arizona Colorado New Hampshire Michigan Nevada Utah Alabama U.S. Wisconsin Tennessee Texas Illinois Washington Georgia Louisiana Virginia North Carolina South Carolina New York Pennsylvania California Florida Indiana Ohio Maryland Connecticut D.C. Delaware Massachusetts New Jersey Rhode Island 25.4 24.9 23.5 21.8 20.6 20.3 18.3 17.1 17 16.7 15.6 13.9 11.4 10.7 10.7 8.6 8.4 8 6.6 6.5 5.9 5.6 5.4 5 4.6 4.2 3.9 3.4 2.4 2.1 2 2 1.4 0.3 0.3 0.3 0.2 0 0 0 0 0 0 39.6 35.9 32.4 48.6 45.4 61.2 57.7 Note: Alaska & Hawaii are not yet included. 0 10 20 30 40 50 60 70 Percent of State Population
% of Population Frontier by State FAR Level 1 Definition Wyoming Montana North Dakota South Dakota Mississippi Nebraska New Mexico Kansas Vermont Iowa Kentucky Idaho Arkansas Minnesota West Virginia Oklahoma Missouri Maine Oregon Arizona Colorado New Hampshire Michigan Nevada Utah Alabama U.S. Wisconsin Tennessee Texas Illinois Washington Georgia Louisiana Virginia North Carolina South Carolina New York Pennsylvania California Florida Indiana Ohio Maryland Connecticut D.C. Delaware Massachusetts New Jersey Rhode Island 25.4 24.9 23.5 21.8 20.6 20.3 18.3 17.1 17 16.7 15.6 13.9 11.4 10.7 10.7 8.6 8.4 8 6.6 6.5 5.9 5.6 5.4 5 4.6 4.2 3.9 3.4 2.4 2.1 2 2 1.4 0.3 0.3 0.3 0.2 0 0 0 0 0 0 39.6 35.9 32.4 48.6 45.4 61.2 57.7 Note: Alaska & Hawaii are not yet included. 0 10 20 30 40 50 60 70 Percent of State Population
# of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Texas (1,130,970) 2. Mississippi (1,122,887) 3. Missouri (935,997) 4. Minnesota (898,620) 5. Kentucky (878,367) 6. Michigan (850,590) 7. Iowa (687,269) 8. Kansas (683,430) U.S. (17,960,713) Note: AK & HI not yet included but neither will make this list)
# of State Popula@on FAR Level 1 (>60 minutes to 50K+) versus Level 4 (more complicated defini*on) 1. Texas (1,130,970) 2. Mississippi (1,122,887) 3. Missouri (935,997) 4. Minnesota (898,620) 5. Kentucky (878,367) 6. Michigan (850,590) 7. Iowa (687,269) 8. Kansas (683,430) U.S. (17,960,713) 1. Minnesota (324,846) 2. Missouri (276,561) 3. Kentucky (242,083) 4. Michigan (228,777) 5. Texas (217,750) 6. Wisconsin (186,360) 7. South Dakota (184,816) 8. Kansas (179,609) U.S. (4,782,328) Note: AK & HI not yet included but neither will make this list)
# of State Popula@on FAR Level 1 (>60 minutes to 50K+) 1. Texas (1,130,970) (28) 2. Mississippi (1,122,887) (5) 3. Missouri (935,997) (17) 4. Minnesota (898,620) (14) 5. Kentucky (878,367) (11) 6. Michigan (850,590) (23) 7. Iowa (687,269) (10) 8. Kansas (683,430) (8) U.S. (17,960,713) % Popula*on Rank Note: AK & HI not yet included
% of State Popula@on FAR Level 1 (>60 minutes to 50K+)/Level 2 (>60 minutes to 50K+ AND > 45 minutes to 25K+) 1. Wyoming (61.2%) 2. Montana (57.7%) 3. North Dakota (48.6%) 4. South Dakota (45.4%) 5. Mississippi (39.6%) 6. Nebraska (35.9%) 7. New Mexico (32.4%) 8. Kansas (25.4%) U.S. (6.5%) 1. Wyoming (61.1%) 2. South Dakota (45.4%) 3. North Dakota (39.1) 4. Montana (27.7%) 5. Nebraska (21.8%) 6. New Mexico (16.9%) 7. Arkansas (16.8%) 8. Kentucky (16.7%) U.S. (4.5%) Note: AK & HI not yet included
% of State Popula@on FAR Level 1 (>60 minutes to 50K+)/Level 4 (4 criteria complicated one) 1. Wyoming (61.2%) 2. Montana (57.7%) 3. North Dakota (48.6%) 4. South Dakota (45.4%) 5. Mississippi (39.6%) 6. Nebraska (35.9%) 7. New Mexico (32.4%) 8. Kansas (25.4%) U.S. (6.5%) 1. North Dakota (26.2%) 2. South Dakota (24.5%) 3. Montana (15.5) 4. Wyoming (12.9%) 5. Nebraska (10.3%) 6. Maine (6.7%) 7. Vermont (6.7%) 8. Kansas (6.7%) U.S. (1.7%) Note: AK & HI not yet included
Gary Hart ary.hart@med.und.edu