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Quality of Life - How does the Midlands stack up? An analysis of Richland & Lexington counties, compared with similar regions across the Southeast June 25, 2020 In your opinion, what factors are most important when thinking about

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Quality of Life -

How does the Midlands stack up?

An analysis of Richland & Lexington counties, compared with similar regions across the Southeast

June 25, 2020

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In your opinion, what factors are most important when thinking about “Quality

  • f Life?”

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Type in Code: 56 13 54

Parker Poe Consulting
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Quality of Life is tricky to measure!

It means different things to different people.

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Parker Poe Consulting
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Quality of Life – What We Studied

– Population Trends & Diversity – Housing & Households – Health & Safety

– Traffic Fatalities – Perceived Health of Population – Violent Crime – Disconnected Youth

– Access to Businesses & Amenities

– Disposable Income – Business Access

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Parker Poe Consulting
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MSAs or Counties?

– MSA à Metropolitan Statistical Area

– Federal designation outlining a region with 50,000+ – Linked by “social and economic factors”

– Commuting patterns, work locations, spending, etc.

– Columbia, SC MSA à

– Calhoun – Fairfield – Kershaw – Lexington – Richland – Saluda

– Counties

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Parker Poe Consulting
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Quality of Life – Where We Studied

Mirrors Midlands Competitiveness Report

Includes Metro Area, Counties, Total Population and Population Density (people per square mile)

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Metro Area “Primary County” “Secondary County” “Additional County” Raleigh, NC 1,294,980 Wake 1,092,305 population 1275 people per sq. mile Johnston 202,675 population 255 people per sq. mile Greenville, SC 839,632 Greenville 514,213 647 people per sq. mile Anderson 200,482 265 people per sq. mile Pickens (Secondary) 124,937 244 people per sq. mile Charleston, SC 787,643 Charleston 404,905 299 people per sq. mile Berkeley 221,091 180 people per sq. mile Dorchester (Secondary) 160,647 279 people per sq. mile Columbia, SC 704,608 Richland 414,576 537 people per sq. mile Lexington 295,032 389 people per sq. mile Greensboro, NC 677,021 Guilford 533,670 811 people per sq. mile Randolph 143,351 182 people per sq. mile Knoxville, TN 596,638 Knox 465,289 885 people per sq. mile Blount 131,349 232 people per sq. mile Winston Salem, NC 545,713 Forsyth 379,099 918 people per sq. mile Davidson 166,614 294 people per sq. mile Augusta, GA 525,246 Richmond 201,554 613 people per sq. mile Aiken (SC) 169,401 157 people per sq. mile Columbia (Primary) 154,291 501 people per sq. mile Lexington, KY 377,700 Fayette 323,780 1132 people per sq. mile Jessamine 53,920 308 people per sq. mile Tallahassee, FL 292,502 Leon 292,502 417 people per sq. mile Parker Poe Consulting
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Population Stats & Diversity

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Parker Poe Consulting
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Population – Overall Migration Trends

Richland County Rank – 8/11 Lexington County Rank – 3/11

About: Data taken from April 1, 2010 to July 1, 2018. T

  • tal Net Migration for time period

per county. Number indicates total number of new residents moving to a particular county.

Source: U.S. Census Bureau, American Community Survey “Estimates of the Components of Resident Population Change” Primary County Secondary County Net Migration 1 Wake (Raleigh, NC) +127,891 2 Greenville (Greenville, SC) +45,048 3 Charleston (Charleston, SC) +40,437 4 Berkeley (Charleston, SC) +31,654 5 Guilford (Greensboro, NC) +29,141 6 Johnston (Raleigh, NC) +26,017 7 Knox (Knoxville, TN) +24,936 8 Lexington (Columbia, SC) +24,879 9 Columbia (Augusta, GA) +22,917 10 Dorchester (Charleston, SC) +17,735 11 Forsyth (Winston Salem, NC) +17,545 12 Richland (Columbia, SC) +14,761 13 Fayette (Lexington, KY) +13,113 14 Anderson (Greenville, SC) +12,111 15 Blount (Knoxville, TN) +8,878 16 Aiken, SC (Augusta, GA) +7,416 17 Leon (Tallahassee, FL) +6,602 18 Pickens (Greenville, SC) +4,971 19 Davidson (Winston Salem, NC) +3,709 20 Jessamine (Lexington, KY) +3,317 21 Randolph (Greensboro, NC) +347 22 Richmond (Augusta, GA)
  • 7,181
Parker Poe Consulting
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Population – Domestic Migration Trends

Richland County Rank – 8/11 Lexington County Rank – 3/11

About: Data taken from April 1, 2010 to July 1, 2018. T

  • tal Net Migration for time period

per county. Number indicates total number of new residents moving to a particular county.

Source: U.S. Census Bureau, American Community Survey “Estimates of the Components of Resident Population Change” Primary County Secondary County Net Migration 1 Wake (Raleigh, NC) +97,063 2 Charleston (Charleston, SC) +37,443 3 Greenville (Greenville, SC) +36,326 4 Berkeley (Charleston, SC) +31,654 5 Johnston (Raleigh, NC) +25,087 6 Lexington (Columbia, SC) +21,255 7 Columbia (Augusta, GA) +21,016 8 Knox (Knoxville, TN) +20,704 9 Dorchester (Charleston, SC) +16,628 10 Guilford (Greensboro, NC) +15,671 11 Forsyth (Winston Salem, NC) +13,845 12 Anderson (Greenville, SC) +11,089 13 Blount (Knoxville, TN) +8,396 14 Richland (Columbia, SC) +7,090 15 Aiken, SC (Augusta, GA) +6,497 16 Davidson (Winston Salem, NC) +3,279 17 Pickens (Greenville, SC) +3,131 18 Jessamine (Lexington, KY) +2,525 19 Fayette (Lexington, KY) +1,983 20 Leon (Tallahassee, FL) +451 21 Randolph (Greensboro, NC)
  • 87
22 Richmond (Augusta, GA)
  • 9,736
Parker Poe Consulting
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Population – International Migration Trends

Richland County Rank – 8/11 Lexington County Rank – 3/11

About: Data taken from April 1, 2010 to July 1, 2018. T

  • tal Net Migration for time period

per county. Number indicates total number of new residents moving to a particular county.

Source: U.S. Census Bureau, American Community Survey “Estimates of the Components of Resident Population Change” Primary County Secondary County Net Migration 1 Wake (Raleigh, NC) +30,828 2 Guilford (Greensboro, NC) +13,470 3 Fayette (Lexington, KY) +11,130 4 Greenville (Greenville, SC) +8,722 5 Richland (Columbia, SC) +7,671 6 Leon (Tallahassee, FL) +6,151 7 Knox (Knoxville, TN) +4,232 8 Forsyth (Winston Salem, NC) +3,700 9 Lexington (Columbia, SC) +3,624 10 Berkeley (Charleston, SC) +3,100 11 Charleston (Charleston, SC) +2,994 12 Richmond (Augusta, GA) +2,555 13 Columbia (Augusta, GA) +1,901 14 Pickens (Greenville, SC) +1,840 15 Dorchester (Charleston, SC) +1,107 16 Anderson (Greenville, SC) +1,022 17 Johnston (Raleigh, NC) +930 18 Aiken, SC (Augusta, GA) +919 19 Jessamine (Lexington, KY) +792 20 Blount (Knoxville, TN) +482 21 Randolph (Greensboro, NC) +434 22 Davidson (Winston Salem) +430 Parker Poe Consulting
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Diversity Index

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Richland County Rank – 4/11 Lexington County Rank – 6/11

About: ESRI's Diversity Index captures the racial and ethnic diversity of a geographic area in a single number, from 0 to 100. The Diversity Index allows for efficient analysis and mapping of seven race groups that can be either of Hispanic or non-Hispanic

  • rigin—a total of 14 separate race/ethnic
  • groupings. The Diversity Index from

Esri represents the likelihood that two persons, chosen at random from the same area, belong to different race or ethnic

  • groups. Ethnic diversity, as well as

racial diversity, is included in the definition of the Diversity Index. A higher number indicates a more diverse population.

Source: ESRI Community Analyst 10 20 30 40 50 60 70 80

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Primary Secondary

Parker Poe Consulting
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Housing & Households

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Parker Poe Consulting
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% Households Below Poverty Level

Richland County Rank – 7/11 Lexington County Rank – 2/11

About: The number of households who are below the poverty level. Poverty status is determined by comparing the person’s total family income in the last 12 months with the poverty threshold appropriate for that person's family size and composition. If the total income of that person's family is less than the threshold appropriate for that family, then the person is considered “below the poverty level." The American Community Survey (ACS) period estimates are based on a rolling sample survey spanning a 60- month period. A Margin of Error (MOE) measures the variability of the estimate due to sampling error. Esri's Reliability measure designates the usability of the estimate

Source: ESRI Community Analyst 2014-2018 Primary County Secondary County % of Households Below Poverty Level 1 Columbia (Augusta, GA) 7.62% 2 Wake (Raleigh, NC) 8.58% 3 Berkeley (Charleston, SC) 11.51% 4 Lexington (Columbia, SC) 11.65% 5 Johnston (Raleigh, NC) 11.82% 6 Dorchester (Charleston, SC) 11.99% 7 Blount (Knoxville, TN) 12.02% 8 Greenville (Greenville, SC) 12.29% 9 Charleston (Charleston, SC) 13.51% 10 Randolph (Greensboro, NC) 14.68% 11 Guilford (Greensboro, NC) 14.69% 12 Knox (Knoxville, TN) 14.72% 13 Davidson (Winston Salem, NC) 14.82% 14 Anderson (Greenville, SC) 15.40% 15 Aiken, SC (Augusta, GA) 15.45% 16 Richland (Columbia, SC) 15.83% 17 Jessamine (Lexington, KY) 15.97% 18 Forsythe (Winston Salem, NC) 16.05% 19 Fayette (Lexington, KY) 16.44% 20 Pickens (Greenville, SC) 17.04% 21 Leon (Tallahassee, FL) 19.27% 22 Richmond (Augusta, GA) 21.29% Parker Poe Consulting
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Household Disposable Income

Richland County Rank – 8/11 Lexington County Rank – 4/11

About: Current-year estimate of average disposable income. It is computed by dividing aggregate disposable income by all households with disposable income. Disposable income represents money income after taxes. Four types of taxes are deducted: federal individual income taxes, state individual income taxes, FICA (Social Security) and federal retirement payroll taxes, and property taxes for owner-

  • ccupied housing.
Source: ESRI Community Analyst 2019 Primary County Secondary County Average Disposable Income 1 Wake (Raleigh, NC) $78,206 2 Columbia (Augusta, GA) $72,242 3 Charleston (Charleston, SC) $69,105 4 Jessamine (Lexington, KY) $64,820 5 Dorchester (Charleston, SC) $64,084 6 Knox (Knoxville, TN) $63,656 7 Fayette (Lexington, KY) $62,529 8 Berkeley (Charleston, SC) $62,177 9 Greenville (Greenville, SC) $62,025 10 Lexington (Columbia, SC) $61,600 11 Leon (Tallahassee, FL) $61,515 12 Johnston (Raleigh, NC) $58,702 13 Richland (Columbia, SC) $58,333 14 Guilford (Greensboro, NC) $57,865 15 Blount (Knoxville, TN) $57,795 16 Forsyth (Winston Salem, NC) $57,460 17 Pickens (Greenville, SC) $53,318 18 Anderson (Greenville, SC) $52,983 19 Aiken, SC (Augusta, GA) $52,600 20 Davidson (Winston Salem, NC) $49,893 21 Randolph (Greensboro, NC) $47,215 22 Richmond (Augusta, GA) $44,842 Parker Poe Consulting
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Housing Affordability Index

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Richland County Rank – 5/11 Lexington County Rank – 1/11

About: The Housing Affordability Index measures the likelihood that a family in the county earns enough income to qualify for a mortgage loan on a typical home at the national and regional levels based on the most recent data regarding price and income. Index value above 100 means families have more than enough income to qualify for a mortgage loan, assuming a down payment of 20% of the home price and a qualifying ratio of 25%. The higher the index rating, the more likely it is that a family can afford to purchase a house. Source: ESRI Community Analyst

Parker Poe Consulting
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Housing Vacancy Rates

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Richland County Rank – 4/11 Lexington County Rank – 8/11

About: Current-year estimate of total housing units and vacant housing units. A housing unit is a house, an apartment, a mobile home, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters. Separate living quarters are those in which the occupants live separately from any other people in the building and which have direct access from the outside of the building or through a common hall. Occupants may be a single family, one person living alone, two or more families living together, or any other group of related or unrelated people who share living
  • arrangements. A vacant housing unit is classified as
no one living in the dwelling, unless its occupant or
  • ccupants are only temporarily absent—such as
away on vacation, in the hospital for a short stay, or
  • n a business trip—and will be returning.
Source: ESRI Community Analyst 2019 Parker Poe Consulting
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Commute Time – Primary County

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Richland County Rank – T4/11

(1/11 indicates shortest commuting time) About: Data represents the average commuting times in minutes experienced by workers within the county (2017). Source: US Census Bureau, American Community Survey (2017) (Commuting Characteristics)

Parker Poe Consulting
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Commute Time – Secondary County

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Lexington County Rank – 8/11

(1/11 indicates shortest commuting time)

About: Data represents the average commuting times in minutes experienced by workers within the county (2017).

Source: US Census Bureau, American Community Survey (2017) (Commuting Characteristics)

Parker Poe Consulting
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Households without Vehicles

Richland County Rank – 6/11 Lexington County Rank – 11/11 About: The American Community Survey (ACS) period estimates are based on a rolling sample survey spanning a 60-month period. A Margin

  • f Error (MOE) measures the

variability of the estimate due to sampling error. Esri's Reliability measure designates the usability of the estimate.

Source: ESRI Community Analyst 2014-2018 Primary County Secondary County Households % of total Households 1 Jessamine (Lexington, KY) 238 2.01% 2 Columbia (Augusta, GA) 538 1.45% 3 Dorchester (Charleston, SC) 830 2.13% 4 Blount (Knoxville, TN) 844 2.24% 5 Pickens (Greenville, SC) 973 3.04% 6 Johnston (Raleigh, NC) 989 2.06% 7 Randolph (Greensboro, NC) 1,013 2.52% 8 Richmond (Augusta, GA) 1,027 2.67% 9 Davidson (Winston Salem, NC) 1,184 2.58% 10 Fayette (Lexington, KY) 1,300 1.85% 11 Leon (Tallahassee, FL) 1,367 2.28% 12 Berkeley (Charleston, SC) 1,383 2.57% 13 Aiken, SC (Augusta, GA) 1,486 3.11% 14 Anderson (Greenville, SC) 1,493 2.78% 15 Lexington (Columbia, SC) 1,511 1.84% 16 Forsyth (Winston Salem, NC) 1,867 2.07% 17 Richland (Columbia, SC) 2,457 2.78% 18 Guilford (Greensboro, NC) 2,490 2.08% 19 Charleston (Charleston, SC) 2,593 2.71% 20 Knox (Knoxville, TN) 2,594 2.19% 21 Greenville (Greenville, SC) 2,954 2.35% 22 Wake (Raleigh, NC) 3,114 1.25% Parker Poe Consulting
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% Households With No Internet Access

Richland County Rank – 9/11 Lexington County Rank – 4/11

About: % of total households that have no access to internet.

Source: ESRI Community Analyst, American Community Survey 2014-2018 Primary County Secondary County % of Households Without Internet 1 Columbia (Augusta, GA) 6.99% 2 Wake (Raleigh, NC) 10.02% 3 Charleston (Charleston, SC) 11.72% 4 Greenville (Greenville, SC) 14.97% 5 Pickens (Greenville, SC) 15.15% 6 Berkeley (Charleston, SC) 15.45% 7 Fayette (Lexington, KY) 15.65% 8 Forsyth (Winston Salem, NC) 15.70% 9 Blount (Knoxville, TN) 16.28% 10 Lexington (Columbia, SC) 16.38% 11 Dorchester (Charleston, SC) 17.09% 12 Knox (Knoxville, TN) 17.47% 13 Leon (Tallahassee, FL) 17.68% 14 Richland (Columbia, SC) 18.01% 15 Johnston (Raleigh, NC) 19.74% 16 Aiken, SC (Augusta, GA) 20.21% 17 Anderson (Greenville, SC) 20.37% 18 Guilford (Greensboro, NC) 20.63% 19 Randolph (Greensboro, NC) 21.32% 20 Davidson (Winston Salem, NC) 21,87% 21 Jessamine (Lexington, KY) 22.88% 22 Richmond (Augusta, GA) 23.64% Parker Poe Consulting
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Health & Safety

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Parker Poe Consulting
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Disconnected Youth

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Richland County Rank – T9/11 Lexington County Rank – T5/11

(1/11 indicates highest % of disconnected youth)

About: Youth Disconnection portrays a dynamic between individuals and their context. Disconnected youth are at an increased risk of violent behavior, smoking, and other detrimental

  • behavior. This is a percentage of

teens and young adults (ages 16- 19) who are neither working nor in school.

Source: County Health Rankings 2019.

Parker Poe Consulting
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Traffic Fatalities

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Richland County Rank – 7/11 Lexington County Rank – T5/11

(1/11 indicates fewest number of traffic fatalities)

About: Data represents the Motor Vehicle Mortality Rate (traffic fatalities) per 100,000 residents per year.

Source: CountyHealthRankings.org “Motor Vehicle Crash Deaths”; Compressed Mortality File (CMF) 2011-2017

Parker Poe Consulting
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Households Receiving Food Stamps / SNAP Benefits

Richland County Rank – 9/11 Lexington County Rank – 4/11 About: The American Community Survey (ACS) period estimates are based on a rolling sample survey spanning a 60-month

  • period. A Margin of Error (MOE) measures

the variability of the estimate due to sampling

  • error. Esri's Reliability measure designates

the usability of the estimate.

Source: ESRI Community Analyst (ACS) 2014-2018 Primary County Secondary County % of total Households Households w/ Food Stamps 1 Columbia (Augusta, GA) 5.15% 2,410 2 Wake (Raleigh, NC) 6.42% 25,087 3 Charleston (Charleston, SC) 8.88% 13,902 4 Greenville (Greenville, SC) 9.73% 18,427 5 Pickens (Greenville, SC) 9.97% 4,721 6 Berkeley (Charleston, SC) 10.37% 7,770 7 Fayette (Lexington, KY) 10.42% 13,424 8 Forsyth (Winston Salem, NC) 11.38% 16,697 9 Blount (Knoxville, TN) 11.56% 5,796 10 Lexington (Columbia, SC) 11.63% 12,939 11 Dorchester (Charleston, SC) 11.89% 6,487 12 Knox (Knoxville, TN) 11.99% 21,981 13 Leon (Tallahassee, FL) 12.21% 13,787 14 Richland (Columbia, SC) 13.68% 20,561 15 Johnston (Raleigh, NC) 13.76% 9,241 16 Aiken, SC (Augusta, GA) 13.82% 9,217 17 Anderson (Greenville, SC) 13.83% 10,595 18 Guilford (Greensboro, NC) 14.39% 29,179 19 Randolph (Greensboro, NC) 14.78% 8,282 20 Davidson (Winston Salem, NC) 15.58% 10,202 21 Jessamine (Lexington, KY) 16.33% 3,066 22 Richmond (Augusta, GA) 21.06% 15,196 Parker Poe Consulting
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% of Population – Perceived Poor or Fair Health

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Richland County Rank – T3/11 Lexington County Rank – T1/11

(1 indicates lowest % of population in fair or poor health)

About: Self Reported health-status is a general measure of health-related quality of life in a

  • population. The use of self-rated health is a

measure to compare health status benefits. Data graphed represents the county percentage

  • f adults who consider themselves to be in poor
  • r fair health. Age is a non-modifiable risk factor,

and as age increases, poor health outcomes are more likely. Source: County Health Rankings 2019

Parker Poe Consulting
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Violent Crime – Primary Counties

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Richland County Rank Among Tier I – 11/11

(1/11 indicates lowest % of violent crime) About: Number of violent crimes per 100.000

  • population. Rates measure the number of

events in a given time period divided by the average number of people at risk during that period.

Source: County Health Rankings 2019 (Data used for 2019 reports was pulled from 2014 and 2016 data). The Uniform Crime Reporting (UCR) Program was conceived in 1929 by the International Association of Chiefs of Police to meet a need for reliable, uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those
  • statistics. Today, several annual statistical
publications, such as the comprehensive Crime in the United States, are produced from data provided by nearly 17,000 law enforcement agencies across the United States. The County Health Rankings use data from the County-Level Detailed Arrest and Offense Data report. Parker Poe Consulting
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Violent Crime – Secondary Counties

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Lexington County Rank – 7/11

(1/11 indicates lowest % of violent crime) About: Number of violent crimes per 100.000

  • population. Rates measure the number of

events (births, death, etc..) in a given time period divided by the average number of people at risk during that period.

Source: County Health Rankings 2019 (Data used for 2019 reports was pulled from 2014 and 2016 data). The Uniform Crime Reporting (UCR) Program was conceived in 1929 by the International Association of Chiefs of Police to meet a need for reliable, uniform crime statistics for the nation. In 1930, the FBI was tasked with collecting, publishing, and archiving those
  • statistics. Today, several annual statistical
publications, such as the comprehensive Crime in the United States, are produced from data provided by nearly 17,000 law enforcement agencies across the United States. The County Health Rankings use data from the County-Level Detailed Arrest and Offense Data report. Parker Poe Consulting
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Access to Businesses & Amenities

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Parker Poe Consulting
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Options vs. Convenience

Options – Citizens per Location Convenience – Locations per Square Mile

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Parker Poe Consulting
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Options: Restaurants & Bars

Citizens per Location, Food Service & Drinking Places

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Columbia, SC Region – 9/10

(1/10 indicates fewest number of citizens per food and drinking place, evidencing greater dining & drinking options)

About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

Parker Poe Consulting
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Options: Arts, Entertainment & Recreation

Citizens per Location

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Columbia, SC Region – 9/10

(1/10 indicates fewest number of citizens per location, evidencing greater recreation options)

About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

Parker Poe Consulting
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Options: Sporting Goods, Hobby & Music Stores

Citizens per Location

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Columbia, SC Region – 10/10

(1/10 indicates fewest number of citizens per location, evidencing greater options)

About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

Parker Poe Consulting
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Options: Clothing & Clothing Accessory Stores

Citizens per Location

33

Columbia, SC Region – 5/10

(1/10 indicates fewest number of citizens per location, evidencing options)

About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

Parker Poe Consulting
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Options: Health Care & Social Assistance

Citizens per Location

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Columbia, SC Region – 9/10

(1/10 indicates fewest number of citizens per location, evidencing greater options for healthcare and social assistance)

About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

Parker Poe Consulting
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Convenience: Food and Beverage Stores

  • Sq. Miles per Location

Richland County Rank – 8/11

(1/11 indicates highest concentration of grocery & beverage stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

35

Parker Poe Consulting
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Convenience: Food and Beverage Stores

  • Sq. Miles per Location

Lexington County Rank – 1/11

(1/11 indicates highest concentration of grocery & beverage stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

36

Parker Poe Consulting
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Convenience: General Merchandise Stores

  • Sq. Miles per Location

Richland County Rank – 8/11

(1/11 indicates highest concentration of general merchandise stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

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Parker Poe Consulting
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Convenience: General Merchandise Stores

  • Sq. Miles per Location

Lexington County Rank – 1/11

(1/11 indicates highest concentration of general merchandise stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

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Parker Poe Consulting
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Convenience: Health & Personal Care Stores

  • Sq. Miles per Location

Richland County Rank – 8/11

(1/11 indicates highest concentration of health & personal care stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

39

Parker Poe Consulting
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Convenience: Health & Personal Care Stores

  • Sq. Miles per Location

Lexington County Rank – 1/11

(1/11 indicates highest concentration of health & personal care stores based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

40

Parker Poe Consulting
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Convenience: Gas Stations

  • Sq. Miles per Location

Richland County Rank – 7/11

(1/11 indicates highest concentration of gas stations based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

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Convenience: Gas Stations

  • Sq. Miles per Location

Lexington County Rank – 1/11

(1/11 indicates highest concentration of gas stations based on area in square miles) About: Esri Total Residential Population forecasts for 2019. Date Note: Data on the Business Summary report is calculated using Esri’s Data allocation method which uses census block groups to allocate business summary data to custom areas. Source: ESRI Community Analyst, ARCGIS

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A few closing thoughts…

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Q&A

Morgan Crapps

morgan@parkerpoeconsulting.com (803) 542-4571

Azad Khan azad@parkerpoeconsulting.com 803-253-6864

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