City
(
type: esriFieldTypeString, alias: City, length: 1073741822
)
State
(
type: esriFieldTypeString, alias: State, length: 1073741822
)
Teeth
(
type: esriFieldTypeDouble, alias: All teeth lost among adults (65 years and over)
)
Arth
(
type: esriFieldTypeDouble, alias: Arthritis among adults (18 years and over)
)
BingeD
(
type: esriFieldTypeDouble, alias: Binge drinking among adults (18 years and over)
)
Cancer
(
type: esriFieldTypeDouble, alias: Cancer (excluding skin cancer) among adults (18 years and over)
)
Kidney
(
type: esriFieldTypeDouble, alias: Chronic kidney disease among adults (18 years and over)
)
COPD
(
type: esriFieldTypeDouble, alias: Chronic obstructive pulmonary disease among adults (18 years and over)
)
Heart
(
type: esriFieldTypeDouble, alias: Coronary heart disease among adults (18 years and over)
)
Asthma
(
type: esriFieldTypeDouble, alias: Current asthma among adults (18 years and over)
)
LackIns
(
type: esriFieldTypeDouble, alias: Current lack of health insurance among adults (18–64 years)
)
Smoke
(
type: esriFieldTypeDouble, alias: Current smoking among adults (18 years and over)
)
Diab
(
type: esriFieldTypeDouble, alias: Diagnosed diabetes among adults (18 years and over)
)
FOBTest
(
type: esriFieldTypeDouble, alias: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
MamTest
(
type: esriFieldTypeDouble, alias: Mammography use among women (50–74 years)
)
Mental
(
type: esriFieldTypeDouble, alias: Mental health not good for 14 or more days among adults (18 years and over)
)
NoLes
(
type: esriFieldTypeDouble, alias: No leisure-time physical activity among adults (18 years and over)
)
Obese
(
type: esriFieldTypeDouble, alias: Obesity among adults (18 years and over)
)
MPrev
(
type: esriFieldTypeDouble, alias: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
Fprev
(
type: esriFieldTypeDouble, alias: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
Pap
(
type: esriFieldTypeDouble, alias: Papanicolaou smear use among adult women (21–65 years)
)
Health
(
type: esriFieldTypeDouble, alias: Physical health not good for 14 or more days among adults (18 years and over)
)
Sleep
(
type: esriFieldTypeDouble, alias: Sleeping less than 7 hours among adults (18 years and over)
)
Stroke
(
type: esriFieldTypeDouble, alias: Stroke among adults (18 years and over)
)
Vdent
(
type: esriFieldTypeDouble, alias: Visits to dentist or dental clinic among adults (18 years and over)
)
Vdoc
(
type: esriFieldTypeDouble, alias: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
HRank
(
type: esriFieldTypeInteger, alias: 500 Cities Health Rank
)
RTeeth
(
type: esriFieldTypeInteger, alias: RANK: All teeth lost among adults (65 years and over)
)
RArth
(
type: esriFieldTypeInteger, alias: RANK: Arthritis among adults (18 years and over)
)
RBingeD
(
type: esriFieldTypeInteger, alias: RANK: Binge drinking among adults (18 years and over)
)
RCancer
(
type: esriFieldTypeInteger, alias: RANK: Cancer (excluding skin cancer) among adults (18 years and over)
)
RKidney
(
type: esriFieldTypeInteger, alias: RANK: Chronic kidney disease among adults (18 years and over)
)
RCOPD
(
type: esriFieldTypeInteger, alias: RANK: Chronic obstructive pulmonary disease among adults (18 years and over)
)
RHeart
(
type: esriFieldTypeInteger, alias: RANK: Coronary heart disease among adults (18 years and over)
)
RAsthma
(
type: esriFieldTypeInteger, alias: RANK: Current asthma among adults (18 years and over)
)
RLackIns
(
type: esriFieldTypeInteger, alias: RANK: Current lack of health insurance among adults (18–64 years)
)
RSmoke
(
type: esriFieldTypeInteger, alias: RANK: Current smoking among adults (18 years and over)
)
RDiab
(
type: esriFieldTypeInteger, alias: RANK: Diagnosed diabetes among adults (18 years and over)
)
RFOBTest
(
type: esriFieldTypeInteger, alias: RANK: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
RMamTest
(
type: esriFieldTypeInteger, alias: RANK: Mammography use among women (50–74 years)
)
RMental
(
type: esriFieldTypeInteger, alias: RANK: Mental health not good for 14 or more days among adults (18 years and over)
)
RNoLes
(
type: esriFieldTypeInteger, alias: RANK: No leisure-time physical activity among adults (18 years and over)
)
RObese
(
type: esriFieldTypeInteger, alias: RANK: Obesity among adults (18 years and over)
)
RMPrev
(
type: esriFieldTypeInteger, alias: RANK: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
RFprev
(
type: esriFieldTypeInteger, alias: RANK: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
RPap
(
type: esriFieldTypeInteger, alias: RANK: Papanicolaou smear use among adult women (21–65 years)
)
RHealth
(
type: esriFieldTypeInteger, alias: RANK: Physical health not good for 14 or more days among adults (18 years and over)
)
Rsleep
(
type: esriFieldTypeInteger, alias: RANK: Sleeping less than 7 hours among adults (18 years and over)
)
RStroke
(
type: esriFieldTypeInteger, alias: RANK: Stroke among adults (18 years and over)
)
RVdent
(
type: esriFieldTypeInteger, alias: RANK: Visits to dentist or dental clinic among adults (18 years and over)
)
RVdoc
(
type: esriFieldTypeInteger, alias: RANK: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
Teeth
(
type: esriFieldTypeDouble, alias: All teeth lost among adults (65 years and over)
)
Arth
(
type: esriFieldTypeDouble, alias: Arthritis among adults (18 years and over)
)
BingeD
(
type: esriFieldTypeDouble, alias: Binge drinking among adults (18 years and over)
)
Cancer
(
type: esriFieldTypeDouble, alias: Cancer (excluding skin cancer) among adults (18 years and over)
)
Kidney
(
type: esriFieldTypeDouble, alias: Chronic kidney disease among adults (18 years and over)
)
COPD
(
type: esriFieldTypeDouble, alias: Chronic obstructive pulmonary disease among adults (18 years and over)
)
Heart
(
type: esriFieldTypeDouble, alias: Coronary heart disease among adults (18 years and over)
)
Asthma
(
type: esriFieldTypeDouble, alias: Current asthma among adults (18 years and over)
)
LackIns
(
type: esriFieldTypeDouble, alias: Current lack of health insurance among adults (18–64 years)
)
Smoke
(
type: esriFieldTypeDouble, alias: Current smoking among adults (18 years and over)
)
Diab
(
type: esriFieldTypeDouble, alias: Diagnosed diabetes among adults (18 years and over)
)
FOBTest
(
type: esriFieldTypeDouble, alias: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
MamTest
(
type: esriFieldTypeDouble, alias: Mammography use among women (50–74 years)
)
Mental
(
type: esriFieldTypeDouble, alias: Mental health not good for 14 or more days among adults (18 years and over)
)
NoLes
(
type: esriFieldTypeDouble, alias: No leisure-time physical activity among adults (18 years and over)
)
Obese
(
type: esriFieldTypeDouble, alias: Obesity among adults (18 years and over)
)
MPrev
(
type: esriFieldTypeDouble, alias: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
Fprev
(
type: esriFieldTypeDouble, alias: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
Pap
(
type: esriFieldTypeDouble, alias: Papanicolaou smear use among adult women (21–65 years)
)
Health
(
type: esriFieldTypeDouble, alias: Physical health not good for 14 or more days among adults (18 years and over)
)
Sleep
(
type: esriFieldTypeDouble, alias: Sleeping less than 7 hours among adults (18 years and over)
)
Stroke
(
type: esriFieldTypeDouble, alias: Stroke among adults (18 years and over)
)
Vdent
(
type: esriFieldTypeDouble, alias: Visits to dentist or dental clinic among adults (18 years and over)
)
Vdoc
(
type: esriFieldTypeDouble, alias: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
PRnkAll
(
type: esriFieldTypeDouble, alias: Percentile Rank: Overall Health
)
PrnkTeet
(
type: esriFieldTypeDouble, alias: Percentile Rank: All teeth lost among adults (65 years and over)
)
PrnkArth
(
type: esriFieldTypeDouble, alias: Percentile Rank: Arthritis among adults (18 years and over)
)
PrnkBing
(
type: esriFieldTypeDouble, alias: Percentile Rank: Binge drinking among adults (18 years and over)
)
PrnkCanc
(
type: esriFieldTypeDouble, alias: Percentile Rank: Cancer (excluding skin cancer) among adults (18 years and over)
)
PrnkKidn
(
type: esriFieldTypeDouble, alias: Percentile Rank: Chronic kidney disease among adults (18 years and over)
)
PrnkCOPD
(
type: esriFieldTypeDouble, alias: Percentile Rank: Chronic obstructive pulmonary disease among adults (18 years and over)
)
PrnkHear
(
type: esriFieldTypeDouble, alias: Percentile Rank: Coronary heart disease among adults (18 years and over)
)
PrnkAsth
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current asthma among adults (18 years and over)
)
PrnkLack
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current lack of health insurance among adults (18–64 years)
)
PrnkSmok
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current smoking among adults (18 years and over)
)
PrnkDiab
(
type: esriFieldTypeDouble, alias: Percentile Rank: Diagnosed diabetes among adults (18 years and over)
)
PrnkFOBT
(
type: esriFieldTypeDouble, alias: Percentile Rank: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
PrnkMamT
(
type: esriFieldTypeDouble, alias: Percentile Rank: Mammography use among women (50–74 years)
)
PrnkMent
(
type: esriFieldTypeDouble, alias: Percentile Rank: Mental health not good for 14 or more days among adults (18 years and over)
)
PrnkNoLe
(
type: esriFieldTypeDouble, alias: Percentile Rank: No leisure-time physical activity among adults (18 years and over)
)
PrnkObes
(
type: esriFieldTypeDouble, alias: Percentile Rank: Obesity among adults (18 years and over)
)
PrnkMPre
(
type: esriFieldTypeDouble, alias: Percentile Rank: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
PrnkFpre
(
type: esriFieldTypeDouble, alias: Percentile Rank: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
PrnkPap
(
type: esriFieldTypeDouble, alias: Percentile Rank: Papanicolaou smear use among adult women (21–65 years)
)
PrnkHeal
(
type: esriFieldTypeDouble, alias: Percentile Rank: Physical health not good for 14 or more days among adults (18 years and over)
)
PrnkSlee
(
type: esriFieldTypeDouble, alias: Percentile Rank: Sleeping less than 7 hours among adults (18 years and over)
)
PrnkStro
(
type: esriFieldTypeDouble, alias: Percentile Rank: Stroke among adults (18 years and over)
)
PrnkVden
(
type: esriFieldTypeDouble, alias: Percentile Rank: Visits to dentist or dental clinic among adults (18 years and over)
)
PrnkVdoc
(
type: esriFieldTypeDouble, alias: Percentile Rank: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
City
(
type: esriFieldTypeString, alias: City, length: 1073741822
)
State
(
type: esriFieldTypeString, alias: State, length: 1073741822
)
Teeth
(
type: esriFieldTypeDouble, alias: All teeth lost among adults (65 years and over)
)
Arth
(
type: esriFieldTypeDouble, alias: Arthritis among adults (18 years and over)
)
BingeD
(
type: esriFieldTypeDouble, alias: Binge drinking among adults (18 years and over)
)
Cancer
(
type: esriFieldTypeDouble, alias: Cancer (excluding skin cancer) among adults (18 years and over)
)
Kidney
(
type: esriFieldTypeDouble, alias: Chronic kidney disease among adults (18 years and over)
)
COPD
(
type: esriFieldTypeDouble, alias: Chronic obstructive pulmonary disease among adults (18 years and over)
)
Heart
(
type: esriFieldTypeDouble, alias: Coronary heart disease among adults (18 years and over)
)
Asthma
(
type: esriFieldTypeDouble, alias: Current asthma among adults (18 years and over)
)
LackIns
(
type: esriFieldTypeDouble, alias: Current lack of health insurance among adults (18–64 years)
)
Smoke
(
type: esriFieldTypeDouble, alias: Current smoking among adults (18 years and over)
)
Diab
(
type: esriFieldTypeDouble, alias: Diagnosed diabetes among adults (18 years and over)
)
FOBTest
(
type: esriFieldTypeDouble, alias: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
MamTest
(
type: esriFieldTypeDouble, alias: Mammography use among women (50–74 years)
)
Mental
(
type: esriFieldTypeDouble, alias: Mental health not good for 14 or more days among adults (18 years and over)
)
NoLes
(
type: esriFieldTypeDouble, alias: No leisure-time physical activity among adults (18 years and over)
)
Obese
(
type: esriFieldTypeDouble, alias: Obesity among adults (18 years and over)
)
MPrev
(
type: esriFieldTypeDouble, alias: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
Fprev
(
type: esriFieldTypeDouble, alias: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
Pap
(
type: esriFieldTypeDouble, alias: Papanicolaou smear use among adult women (21–65 years)
)
Health
(
type: esriFieldTypeDouble, alias: Physical health not good for 14 or more days among adults (18 years and over)
)
Sleep
(
type: esriFieldTypeDouble, alias: Sleeping less than 7 hours among adults (18 years and over)
)
Stroke
(
type: esriFieldTypeDouble, alias: Stroke among adults (18 years and over)
)
Vdent
(
type: esriFieldTypeDouble, alias: Visits to dentist or dental clinic among adults (18 years and over)
)
Vdoc
(
type: esriFieldTypeDouble, alias: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
HRank
(
type: esriFieldTypeInteger, alias: 500 Cities Health Rank
)
RTeeth
(
type: esriFieldTypeInteger, alias: RANK: All teeth lost among adults (65 years and over)
)
RArth
(
type: esriFieldTypeInteger, alias: RANK: Arthritis among adults (18 years and over)
)
RBingeD
(
type: esriFieldTypeInteger, alias: RANK: Binge drinking among adults (18 years and over)
)
RCancer
(
type: esriFieldTypeInteger, alias: RANK: Cancer (excluding skin cancer) among adults (18 years and over)
)
RKidney
(
type: esriFieldTypeInteger, alias: RANK: Chronic kidney disease among adults (18 years and over)
)
RCOPD
(
type: esriFieldTypeInteger, alias: RANK: Chronic obstructive pulmonary disease among adults (18 years and over)
)
RHeart
(
type: esriFieldTypeInteger, alias: RANK: Coronary heart disease among adults (18 years and over)
)
RAsthma
(
type: esriFieldTypeInteger, alias: RANK: Current asthma among adults (18 years and over)
)
RLackIns
(
type: esriFieldTypeInteger, alias: RANK: Current lack of health insurance among adults (18–64 years)
)
RSmoke
(
type: esriFieldTypeInteger, alias: RANK: Current smoking among adults (18 years and over)
)
RDiab
(
type: esriFieldTypeInteger, alias: RANK: Diagnosed diabetes among adults (18 years and over)
)
RFOBTest
(
type: esriFieldTypeInteger, alias: RANK: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults (50–75 years)
)
RMamTest
(
type: esriFieldTypeInteger, alias: RANK: Mammography use among women (50–74 years)
)
RMental
(
type: esriFieldTypeInteger, alias: RANK: Mental health not good for 14 or more days among adults (18 years and over)
)
RNoLes
(
type: esriFieldTypeInteger, alias: RANK: No leisure-time physical activity among adults (18 years and over)
)
RObese
(
type: esriFieldTypeInteger, alias: RANK: Obesity among adults (18 years and over)
)
RMPrev
(
type: esriFieldTypeInteger, alias: RANK: Older adult men (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
RFprev
(
type: esriFieldTypeInteger, alias: RANK: Older adult women (65 years and over) who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
RPap
(
type: esriFieldTypeInteger, alias: RANK: Papanicolaou smear use among adult women (21–65 years)
)
RHealth
(
type: esriFieldTypeInteger, alias: RANK: Physical health not good for 14 or more days among adults (18 years and over)
)
Rsleep
(
type: esriFieldTypeInteger, alias: RANK: Sleeping less than 7 hours among adults (18 years and over)
)
RStroke
(
type: esriFieldTypeInteger, alias: RANK: Stroke among adults (18 years and over)
)
RVdent
(
type: esriFieldTypeInteger, alias: RANK: Visits to dentist or dental clinic among adults (18 years and over)
)
RVdoc
(
type: esriFieldTypeInteger, alias: RANK: Visits to doctor for routine checkup within the past Year among adults (18 years and over)
)
Description: This dataset was derived from 500 Cities data by the Atlanta Regional Commission Research & Analytics Group. The ordinal rankings were calculated among the 131 census tracts in the City of Atlanta by first standardizing (z-score) the crude prevalence rate in each tract for the 28 indicators compiled by the 500 Cities Projejct. The standardized values were then averaged with the three categories (Healthy Outcomes, Prevention, and Unhealthy Behaviors). The averages of the standardized values were then ranked from 1 to 131 to create the category ranks. The Overall Health Rank was determined by calculating the average of the average of the standardized values for the three categories and then ranking the result.
Copyright Text: Center for Disease Control, Atlanta Regional Commission
HealthRank
(
type: esriFieldTypeInteger, alias: Health Rank
)
Arthritis
(
type: esriFieldTypeDouble, alias: Arthritis among adults aged >=18 Years
)
High_blood_pressure
(
type: esriFieldTypeDouble, alias: High blood pressure among adults aged >=18 Years
)
Cancer
(
type: esriFieldTypeDouble, alias: Cancer (excluding skin cancer) among adults aged >=18 Years
)
Asthma
(
type: esriFieldTypeDouble, alias: Current asthma among adults aged >=18 Years
)
Heart_Disease
(
type: esriFieldTypeDouble, alias: Coronary heart disease among adults aged >=18 Years
)
COPD
(
type: esriFieldTypeDouble, alias: Chronic obstructive pulmonary disease among adults aged >=18 Years
)
Diabetes
(
type: esriFieldTypeDouble, alias: Diagnosed diabetes among adults aged >=18 Years
)
High_cholestrol
(
type: esriFieldTypeDouble, alias: High cholesterol among adults aged >=18 Years who have been screened in the past 5 Years
)
Kidney
(
type: esriFieldTypeDouble, alias: Chronic kidney disease among adults aged >=18 Years
)
Mental_Health
(
type: esriFieldTypeDouble, alias: Mental health not good for >=14 days among adults aged >=18 Years
)
Physical_Health
(
type: esriFieldTypeDouble, alias: Physical health not good for >=14 days among adults aged >=18 Years
)
Stroke
(
type: esriFieldTypeDouble, alias: Stroke among adults aged >=18 Years
)
Teeth_loss
(
type: esriFieldTypeDouble, alias: All teeth lost among adults aged >=65 Years
)
Lack_Insurance
(
type: esriFieldTypeDouble, alias: Current lack of health insurance among adults aged 18–64 Years
)
Blood_Pressure_Med
(
type: esriFieldTypeDouble, alias: Taking medicine for high blood pressure control among adults aged >=18 Years with high blood pressure
)
Routine_Doc_Visits
(
type: esriFieldTypeDouble, alias: Visits to doctor for routine checkup within the past Year among adults aged >=18 Years
)
Chol_Screening
(
type: esriFieldTypeDouble, alias: Cholesterol screening among adults aged >=18 Years
)
FecalOccultBloodTest
(
type: esriFieldTypeDouble, alias: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults aged 50–75 Years
)
Older_men_preventative
(
type: esriFieldTypeDouble, alias: Older adult men aged >=65 Years who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
Older_wmn_preventative
(
type: esriFieldTypeDouble, alias: Older adult women aged >=65 Years who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 Years
)
Visits_Dentist
(
type: esriFieldTypeDouble, alias: Visits to dentist or dental clinic among adults aged >=18 Years
)
Mammograph
(
type: esriFieldTypeDouble, alias: Mammography use among women aged 50–74 Years
)
Papanicola
(
type: esriFieldTypeDouble, alias: Papanicolaou smear use among adult women aged 21–65 Years
)
Binge_drinking
(
type: esriFieldTypeDouble, alias: Binge drinking among adults aged >=18 Years
)
Smoking
(
type: esriFieldTypeDouble, alias: Current smoking among adults aged >=18 Years
)
No_leisure
(
type: esriFieldTypeDouble, alias: No leisure-time physical activity among adults aged >=18 Years
)
Obesity
(
type: esriFieldTypeDouble, alias: Obesity among adults aged >=18 Years
)
Sleeping
(
type: esriFieldTypeDouble, alias: Sleeping less than 7 hours among adults aged >=18 Years
)
Description: This feature class includes the census tracts falling within four Georgia cities selected for analysis by Neighborhood Nexus for its 500 Cities Health and Wellness Toolkit. The dataset was derived from 500 Cities data by the Atlanta Regional Commission Research & Analytics Group. The 28 indicator values are crude-prevalence percentages provided within the 500 Cities 2017 dataset.The city-wide ordinal rankings were calculated for the census tracts within each city seperately. The city-wide ordinal rankings were derived by first standardizing (z-score) the crude-prevalence rate in each tract for the 28 indicators compiled by the 500 Cities Projejct. The standardized values were then averaged with the three categories (Healthy Outcomes, Prevention, and Unhealthy Behaviors). The averages of the standardized values were then ranked from 1 to the total number tracts in each city to create the category ranks. The Overall Health Rank was determined by calculating the average of the average of the standardized values for the three categories and then ranking the result. The city-wide ordincal rankings provide composite values for comparing tracts within each of the cities.The percentile rankings for each of the 28 indicaors were calculated across all the census tracts in the 500 cities. The values, ranging from 0 to 100, represent the relative rank of each census tract among all census tracts within the 500 cities analyzed. The percentile rank values provide a relative measure of how each census tract compares to all census tracts analyzed for the 500 Cities project.
Copyright Text: Center for Disease Control, Atlanta Regional Commission
Overall_Health_Rank
(
type: esriFieldTypeInteger, alias: City-wide Overall Health Rank
)
Arthritis
(
type: esriFieldTypeDouble, alias: Arthritis among adults aged 18 years and over
)
High_blood_pressure
(
type: esriFieldTypeInteger, alias: High blood pressure among adults aged 18 years and over
)
Cancer
(
type: esriFieldTypeDouble, alias: Cancer (excluding skin cancer) among adults aged 18 years and over
)
Asthma
(
type: esriFieldTypeDouble, alias: Current asthma among adults aged 18 years and over
)
Heart_Disease
(
type: esriFieldTypeDouble, alias: Coronary heart disease among adults aged 18 years and over
)
COPD
(
type: esriFieldTypeDouble, alias: Chronic obstructive pulmonary disease among adults aged 18 years and over
)
Diabetes
(
type: esriFieldTypeDouble, alias: Diagnosed diabetes among adults aged 18 years and over
)
High_cholestrol
(
type: esriFieldTypeDouble, alias: High cholesterol among adults aged 18 years and over who have been screened in the past 5 years
)
Kidney_Disease
(
type: esriFieldTypeDouble, alias: Chronic kidney disease among adults aged 18 years and over
)
Mental_Health
(
type: esriFieldTypeDouble, alias: Mental health not good for 14 days or more among adults aged 18 years and over
)
Physical_Health
(
type: esriFieldTypeDouble, alias: Physical health not good for 14 days or more among adults aged 18 years and over
)
Stroke
(
type: esriFieldTypeDouble, alias: Stroke among adults aged 18 years and over
)
Teeth_loss
(
type: esriFieldTypeDouble, alias: All teeth lost among adults aged 65 years and over
)
Lack_Insurance
(
type: esriFieldTypeDouble, alias: Current lack of health insurance among adults aged 18–64 years
)
Blood_Pressure_Med
(
type: esriFieldTypeDouble, alias: Taking medicine for high blood pressure control among adults aged 18 years and over with high blood pressure
)
Routine_Doc_Visits
(
type: esriFieldTypeDouble, alias: Visits to doctor for routine checkup within the past Year among adults aged 18 years and over
)
Chol_Screening
(
type: esriFieldTypeDouble, alias: Cholesterol screening among adults aged 18 years and over
)
FecalOccultBloodTest
(
type: esriFieldTypeDouble, alias: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults aged 50–75 years
)
Older_men_preventative
(
type: esriFieldTypeDouble, alias: Older adult men aged 65 years and over who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
Older_wmn_preventative
(
type: esriFieldTypeDouble, alias: Older adult women aged 65 years and over who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 years
)
Visits_Dentist
(
type: esriFieldTypeDouble, alias: Visits to dentist or dental clinic among adults aged 18 years and over
)
Mammograph
(
type: esriFieldTypeDouble, alias: Mammography use among women aged 50–74 years
)
Papanicola
(
type: esriFieldTypeInteger, alias: Papanicolaou smear use among adult women aged 21–65 years
)
Binge_drinking
(
type: esriFieldTypeDouble, alias: Binge drinking among adults aged 18 years and over
)
Smoking
(
type: esriFieldTypeDouble, alias: Current smoking among adults aged 18 years and over
)
No_phys_activity
(
type: esriFieldTypeDouble, alias: No leisure-time physical activity among adults aged 18 years and over
)
Obesity
(
type: esriFieldTypeDouble, alias: Obesity among adults aged 18 years and over
)
Sleeping
(
type: esriFieldTypeDouble, alias: Sleeping less than 7 hours among adults aged 18 years and over
)
PR_Teeth_loss
(
type: esriFieldTypeDouble, alias: Percentile Rank: All teeth lost among adults aged 65 years and over
)
PR_Arthritis
(
type: esriFieldTypeDouble, alias: Percentile Rank: Arthritis among adults aged 18 years and over
)
PR_Cancer
(
type: esriFieldTypeDouble, alias: Percentile Rank: Cancer (excluding skin cancer) among adults aged 18 years and over
)
PR_Kidney_Disease
(
type: esriFieldTypeDouble, alias: Percentile Rank: Chronic kidney disease among adults aged 18 years and over
)
PR_COPD
(
type: esriFieldTypeDouble, alias: Percentile Rank: Chronic obstructive pulmonary disease among adults aged 18 years and over
)
PR_Heart_Disease
(
type: esriFieldTypeDouble, alias: Percentile Rank: Coronary heart disease among adults aged 18 years and over
)
PR_Asthma
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current asthma among adults aged 18 years and over
)
PR_Diabetes
(
type: esriFieldTypeDouble, alias: Percentile Rank: Diagnosed diabetes among adults aged 18 years and over
)
PR_High_blood_pressure
(
type: esriFieldTypeDouble, alias: Percentile Rank: High blood pressure among adults aged 18 years and over
)
PR_High_cholestrol
(
type: esriFieldTypeDouble, alias: Percentile Rank: High cholesterol among adults aged 18 years and over who have been screened in the past 5 years
)
PR_Mental_Health
(
type: esriFieldTypeDouble, alias: Percentile Rank: Mental health not good for 14 days or more among adults aged 18 years and over
)
PR_Physical_Health
(
type: esriFieldTypeDouble, alias: Percentile Rank: Physical health not good for 14 days or more among adults aged 18 years and over
)
PR_Stroke
(
type: esriFieldTypeDouble, alias: Percentile Rank: Stroke among adults aged 18 years and over
)
PR_Chol_Screening
(
type: esriFieldTypeDouble, alias: Percentile Rank: Cholesterol screening among adults aged 18 years and over
)
PR_Lack_Insurance
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current lack of health insurance among adults aged 18–64 years
)
PR_FecalOccultBloodTest
(
type: esriFieldTypeDouble, alias: Percentile Rank: Fecal occult blood test, sigmoidoscopy, or colonoscopy among adults aged 50–75 years
)
PR_Mammograph
(
type: esriFieldTypeDouble, alias: Percentile Rank: Mammography use among women aged 50–74 years
)
PR_Older_men_preventative
(
type: esriFieldTypeDouble, alias: Percentile Rank: Older adult men aged 65 years and over who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening
)
PR_Older_wmn_preventative
(
type: esriFieldTypeDouble, alias: Percentile Rank: Older adult women aged 65 years and over who are up to date on a core set of clinical preventive services: Flu shot past Year, PPV shot ever, Colorectal cancer screening, and Mammogram past 2 years
)
PR_Papanicola
(
type: esriFieldTypeDouble, alias: Percentile Rank: Papanicolaou smear use among adult women aged 21–65 years
)
PR_Blood_Pressure_Med
(
type: esriFieldTypeDouble, alias: Percentile Rank: Taking medicine for high blood pressure control among adults aged 18 years and over with high blood pressure
)
PR_Visits_Dentist
(
type: esriFieldTypeDouble, alias: Percentile Rank: Visits to dentist or dental clinic among adults aged 18 years and over
)
PR_Routine_Doc_Visits
(
type: esriFieldTypeDouble, alias: Percentile Rank: Visits to doctor for routine checkup within the past Year among adults aged 18 years and over
)
PR_Binge_drinking
(
type: esriFieldTypeDouble, alias: Percentile Rank: Binge drinking among adults aged 18 years and over
)
PR_Smoking
(
type: esriFieldTypeDouble, alias: Percentile Rank: Current smoking among adults aged 18 years and over
)
PR_No_phys_activity
(
type: esriFieldTypeDouble, alias: Percentile Rank: No leisure-time physical activity among adults aged 18 years and over
)
PR_Obesity
(
type: esriFieldTypeDouble, alias: Percentile Rank: Obesity among adults aged 18 years and over
)
PR_Sleeping
(
type: esriFieldTypeDouble, alias: Percentile Rank: Sleeping less than 7 hours among adults aged 18 years and over
)
Description: This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show various demographic data by census tract in the state of Georgia. This subset includes the following categories which were deemed especially relevant to the 500 Cities health data project as determinants of health outcomes: age, race/ethnicity, income, health insurance, and poverty.The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.Base Attributes:GEOID10 = 2010 Census tract identifier (combination of FIPS codes for state, county, and tract)NAME = 2010 Census tract number and county name- - - - - -Attributes from ACS:Age_Tot_Pop_2016 = Age: # Total population, 2016Pct_Pop_und_age_5_2000 = Age: % Population under age 5, 2000Pct_Pop_und_age_5_2016 = Age: % Population under age 5, 2016ChgPct_Pop_und_age_5_2000_16 = Age: Change, % Population under age 5, 2000-2016Pct_Pop_und_18_2000 = Age: % Population under age 18, 2000Pct_Pop_und_18_2016 = Age: % Population under age 18, 2016ChgPct_Pop_und_18_2000_16 = Age: Change, % Population under age 18, 2000-2016Pct_Pop_ages_18_34_2000 = Age: % Population ages 18-34, 2000Pct_Pop_ages_18_34_2016 = Age: % Population ages 18-34, 2016ChgPct_Pop_ages_18_34_2000_16 = Age: Change, % Population ages 18-34, 2000-2016Pct_Pop_ages_35_49_2000 = Age: % Population ages 35-49, 2000Pct_Pop_ages_35_49_2016 = Age: % Population ages 35-49, 2016ChgPct_Pop_ages_35_49_2000_16 = Age: Change, % Population ages 35-49, 2000-2016Pct_Pop_ages_50_64_2000 = Age: % Population ages 50-64, 2000Pct_Pop_ages_50_64_2016 = Age: % Population ages 50-64, 2016ChgPct_Pop_ages_50_64_2000_16 = Age: Change, % Population ages 50-64, 2000-2016Pct_Pop_ages_65over_2000 = Age: % Population ages 65 and over, 2000Pct_Pop_ages_65over_2016 = Age: % Population ages 65 and over, 2016ChgPct_Pop_ages_65over_2000_16 = Age: Change, % Population ages 65 and over, 2000-2016- - - - - -Race_Tot_Pop_2016 = Race/Ethnicity: # Total population, 2016Pct_NotHisp_White_2016 = Race/Ethnicity: % Not Hispanic, White alone, 2016Pct_NotHisp_White_2000 = Race/Ethnicity: % Not Hispanic, White alone, 2000ChgPct_NonHisp_White_2000_16 = Race/Ethnicity: Change, % Non-Hispanic White, 2000-2016Pct_NotHisp_Black_AA_2016 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016Pct_NotHisp_Black_AA_2000 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000ChgPct_NonHisp_Black_AA_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016Pct_NotHisp_AsianPac_2000 = Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000Pct_NonHisp_AsianPac_2016 = Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016ChgPct_NonHisp_AsianPac_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016Pct_NotHisp_Other_2000 = Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000Pct_NonHisp_Other_2016 = Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016ChgPct_NonHisp_Other_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Other, 2000-2016Pct_HispLat_any_2016 = Race/Ethnicity: % Hispanic or Latino (of any race), 2016Pct_HispLat_all_2000 = Race/Ethnicity: % Hispanic or Latino, all races, 2000ChgPct_HispLat_all_2000_16 = Race/Ethnicity: Change, % Hispanic or Latino all races, 2000-2016- - - - - -HealthIns_Tot_Pop_2016 = Health Insurance: # Total population, 2016Pop_wHealth_Insurance = Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016Pct_Pop_wHealth_Ins = Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016Pop_wPriv_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016Pct_Pop_wPriv_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016Population_with_public_coverage = Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016Pct_Pop_with_public_coverage = Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016Pop_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016Pct_Pop_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016Pop_u18_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pct_Pop_u18_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pop_18to64_Employed = Health Insurance: # Civilian population 18 to 64 years employed, 2016Pop_18to64_Empl_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016Pct_Pop_18to64_Emp_wNo_Hlth_Ins = Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016Pop_18to64_Unemployed = Health Insurance: # Civilian population 18 to 64 years unemployed, 2016Pop_18to64_Unemp_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016Pct_Pop_18to64_Unemp_No_HlthIns = Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016Pop_18to64_Not_in_Labor_Force = Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016Pop_18to64_Not_LabFor_NoHlthIns = Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016PctPop_18to64_NotLFor_NoHlthIns = Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016- - - - - -Income_Tot_Pop_2016 = Income: # Total population, 2016Income_Total_households = Income: # Total Households, 2016Household_inc_less_35k = Income: # Household income less than $35,000, 2016Pct_Household_inc_less_35k = Income: % Household income less than $35,000, 2016Household_inc_35k_75k = Income: # Household income $35,000 to $74,999, 2016Pct_Household_inc_35k_75k = Income: % Household income $35,000 to $74,999, 2016Household_inc_75k_200k = Income: # Household income $75,000 to $199,999, 2016Pct_Household_inc_75k_200k = Income: % Household income $75,000 to $199,999, 2016Household_inc_200k_more = Income: # Household income $200,000 or more, 2016Pct_Household_inc_200k_more = Income: % Household income $200,000 or more, 2016Median_household_Income = Income: Median household income, 2016Median_HH_Income_2000 = Income: Median Household Income, 2000Chg_Median_HH_income_2000_2016 = Income: Change, Median household income, 2000-2016Average_Per_capita_Income = Income: Per capita income (dollars), 2016Aggregate_HH_Income = Income: Aggregate household income, 2016Average_Household_Income = Income: Mean household income, 2016- - - - - -Poverty_Tot_Pop_2016 = Poverty: # Total population, 2016Pop_PovertyStatus_Determined = Poverty: # Population for whom poverty status determined, 2016Population_in_poverty = Poverty: # Population below poverty, 2016Percent_Population_in_poverty = Poverty: % Population below poverty, 2016Population_poverty_2000 = Poverty: # Population below poverty, 2000Pct_Pop_poverty_2000 = Poverty: % Population below poverty, 2000Chg_Pct_Pop_poverty_2000_2016 = Poverty: Change, % Population in poverty, 2000-2016Pop_under18_PovStatusDetermined = Poverty: # Population under 18 years for whom poverty status determined, 2016Pop_under18_in_Poverty = Poverty: # Population under 18 years below poverty, 2016Pct_Pop_under18_in_Poverty = Poverty: % Population under 18 years below poverty, 2016Pop_18_64_PovStatus_Determined = Poverty: # Population 18 to 64 years for whom poverty status determined, 2016Pop_18_64_Years_in_Poverty = Poverty: # Population 18 to 64 years below poverty, 2016Pct_Pop_18_64_Years_in_Poverty = Poverty: % Population 18 to 64 years below poverty, 2016Pop_65older_PovStatusDetermined = Poverty: # Population 65 years and over for whom poverty status determined, 2016Pop_65older_in_Poverty = Poverty: # Population 65 years and over below poverty, 2016Pct_Pop_65older_in_Poverty = Poverty: % Population 65 years and over below poverty, 2016- - - - - -Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016For additional information, please visit the Atlanta Regional Commission atwww.atlantaregional.com.
Copyright Text: U.S. Census Bureau, Atlanta Regional Commission
Description: This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show various demographic data by census tract in the state of Georgia. This subset includes the following categories which were deemed especially relevant to the 500 Cities health data project as determinants of health outcomes: age, race/ethnicity, income, health insurance, and poverty.The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.Base Attributes:GEOID10 = 2010 Census tract identifier (combination of FIPS codes for state, county, and tract)NAME = 2010 Census tract number and county name- - - - - -Attributes from ACS:Age_Tot_Pop_2016 = Age: # Total population, 2016Pct_Pop_und_age_5_2000 = Age: % Population under age 5, 2000Pct_Pop_und_age_5_2016 = Age: % Population under age 5, 2016ChgPct_Pop_und_age_5_2000_16 = Age: Change, % Population under age 5, 2000-2016Pct_Pop_und_18_2000 = Age: % Population under age 18, 2000Pct_Pop_und_18_2016 = Age: % Population under age 18, 2016ChgPct_Pop_und_18_2000_16 = Age: Change, % Population under age 18, 2000-2016Pct_Pop_ages_18_34_2000 = Age: % Population ages 18-34, 2000Pct_Pop_ages_18_34_2016 = Age: % Population ages 18-34, 2016ChgPct_Pop_ages_18_34_2000_16 = Age: Change, % Population ages 18-34, 2000-2016Pct_Pop_ages_35_49_2000 = Age: % Population ages 35-49, 2000Pct_Pop_ages_35_49_2016 = Age: % Population ages 35-49, 2016ChgPct_Pop_ages_35_49_2000_16 = Age: Change, % Population ages 35-49, 2000-2016Pct_Pop_ages_50_64_2000 = Age: % Population ages 50-64, 2000Pct_Pop_ages_50_64_2016 = Age: % Population ages 50-64, 2016ChgPct_Pop_ages_50_64_2000_16 = Age: Change, % Population ages 50-64, 2000-2016Pct_Pop_ages_65over_2000 = Age: % Population ages 65 and over, 2000Pct_Pop_ages_65over_2016 = Age: % Population ages 65 and over, 2016ChgPct_Pop_ages_65over_2000_16 = Age: Change, % Population ages 65 and over, 2000-2016- - - - - -Race_Tot_Pop_2016 = Race/Ethnicity: # Total population, 2016Pct_NotHisp_White_2016 = Race/Ethnicity: % Not Hispanic, White alone, 2016Pct_NotHisp_White_2000 = Race/Ethnicity: % Not Hispanic, White alone, 2000ChgPct_NonHisp_White_2000_16 = Race/Ethnicity: Change, % Non-Hispanic White, 2000-2016Pct_NotHisp_Black_AA_2016 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016Pct_NotHisp_Black_AA_2000 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000ChgPct_NonHisp_Black_AA_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016Pct_NotHisp_AsianPac_2000 = Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000Pct_NonHisp_AsianPac_2016 = Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016ChgPct_NonHisp_AsianPac_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016Pct_NotHisp_Other_2000 = Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000Pct_NonHisp_Other_2016 = Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016ChgPct_NonHisp_Other_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Other, 2000-2016Pct_HispLat_any_2016 = Race/Ethnicity: % Hispanic or Latino (of any race), 2016Pct_HispLat_all_2000 = Race/Ethnicity: % Hispanic or Latino, all races, 2000ChgPct_HispLat_all_2000_16 = Race/Ethnicity: Change, % Hispanic or Latino all races, 2000-2016- - - - - -HealthIns_Tot_Pop_2016 = Health Insurance: # Total population, 2016Pop_wHealth_Insurance = Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016Pct_Pop_wHealth_Ins = Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016Pop_wPriv_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016Pct_Pop_wPriv_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016Population_with_public_coverage = Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016Pct_Pop_with_public_coverage = Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016Pop_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016Pct_Pop_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016Pop_u18_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pct_Pop_u18_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pop_18to64_Employed = Health Insurance: # Civilian population 18 to 64 years employed, 2016Pop_18to64_Empl_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016Pct_Pop_18to64_Emp_wNo_Hlth_Ins = Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016Pop_18to64_Unemployed = Health Insurance: # Civilian population 18 to 64 years unemployed, 2016Pop_18to64_Unemp_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016Pct_Pop_18to64_Unemp_No_HlthIns = Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016Pop_18to64_Not_in_Labor_Force = Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016Pop_18to64_Not_LabFor_NoHlthIns = Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016PctPop_18to64_NotLFor_NoHlthIns = Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016- - - - - -Income_Tot_Pop_2016 = Income: # Total population, 2016Income_Total_households = Income: # Total Households, 2016Household_inc_less_35k = Income: # Household income less than $35,000, 2016Pct_Household_inc_less_35k = Income: % Household income less than $35,000, 2016Household_inc_35k_75k = Income: # Household income $35,000 to $74,999, 2016Pct_Household_inc_35k_75k = Income: % Household income $35,000 to $74,999, 2016Household_inc_75k_200k = Income: # Household income $75,000 to $199,999, 2016Pct_Household_inc_75k_200k = Income: % Household income $75,000 to $199,999, 2016Household_inc_200k_more = Income: # Household income $200,000 or more, 2016Pct_Household_inc_200k_more = Income: % Household income $200,000 or more, 2016Median_household_Income = Income: Median household income, 2016Median_HH_Income_2000 = Income: Median Household Income, 2000Chg_Median_HH_income_2000_2016 = Income: Change, Median household income, 2000-2016Average_Per_capita_Income = Income: Per capita income (dollars), 2016Aggregate_HH_Income = Income: Aggregate household income, 2016Average_Household_Income = Income: Mean household income, 2016- - - - - -Poverty_Tot_Pop_2016 = Poverty: # Total population, 2016Pop_PovertyStatus_Determined = Poverty: # Population for whom poverty status determined, 2016Population_in_poverty = Poverty: # Population below poverty, 2016Percent_Population_in_poverty = Poverty: % Population below poverty, 2016Population_poverty_2000 = Poverty: # Population below poverty, 2000Pct_Pop_poverty_2000 = Poverty: % Population below poverty, 2000Chg_Pct_Pop_poverty_2000_2016 = Poverty: Change, % Population in poverty, 2000-2016Pop_under18_PovStatusDetermined = Poverty: # Population under 18 years for whom poverty status determined, 2016Pop_under18_in_Poverty = Poverty: # Population under 18 years below poverty, 2016Pct_Pop_under18_in_Poverty = Poverty: % Population under 18 years below poverty, 2016Pop_18_64_PovStatus_Determined = Poverty: # Population 18 to 64 years for whom poverty status determined, 2016Pop_18_64_Years_in_Poverty = Poverty: # Population 18 to 64 years below poverty, 2016Pct_Pop_18_64_Years_in_Poverty = Poverty: % Population 18 to 64 years below poverty, 2016Pop_65older_PovStatusDetermined = Poverty: # Population 65 years and over for whom poverty status determined, 2016Pop_65older_in_Poverty = Poverty: # Population 65 years and over below poverty, 2016Pct_Pop_65older_in_Poverty = Poverty: % Population 65 years and over below poverty, 2016- - - - - -Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016For additional information, please visit the Atlanta Regional Commission atwww.atlantaregional.com.
Copyright Text: U.S. Census Bureau, Atlanta Regional Commission
Pct_NotHisp_Black_AA_2016
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016
)
Pct_NotHisp_Black_AA_2000
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000
)
ChgPct_NonHisp_Black_AA_2000_16
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016
)
Pct_NotHisp_AsianPac_2000
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000
)
Pct_NonHisp_AsianPac_2016
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016
)
ChgPct_NonHisp_AsianPac_2000_16
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016
)
Pct_NotHisp_Other_2000
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000
)
Pct_NonHisp_Other_2016
(
type: esriFieldTypeDouble, alias: Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016
)
Description: This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show various demographic data by census tract in the state of Georgia. This subset includes the following categories which were deemed especially relevant to the 500 Cities health data project as determinants of health outcomes: age, race/ethnicity, income, health insurance, and poverty.The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.Base Attributes:GEOID10 = 2010 Census tract identifier (combination of FIPS codes for state, county, and tract)NAME = 2010 Census tract number and county name- - - - - -Attributes from ACS:Age_Tot_Pop_2016 = Age: # Total population, 2016Pct_Pop_und_age_5_2000 = Age: % Population under age 5, 2000Pct_Pop_und_age_5_2016 = Age: % Population under age 5, 2016ChgPct_Pop_und_age_5_2000_16 = Age: Change, % Population under age 5, 2000-2016Pct_Pop_und_18_2000 = Age: % Population under age 18, 2000Pct_Pop_und_18_2016 = Age: % Population under age 18, 2016ChgPct_Pop_und_18_2000_16 = Age: Change, % Population under age 18, 2000-2016Pct_Pop_ages_18_34_2000 = Age: % Population ages 18-34, 2000Pct_Pop_ages_18_34_2016 = Age: % Population ages 18-34, 2016ChgPct_Pop_ages_18_34_2000_16 = Age: Change, % Population ages 18-34, 2000-2016Pct_Pop_ages_35_49_2000 = Age: % Population ages 35-49, 2000Pct_Pop_ages_35_49_2016 = Age: % Population ages 35-49, 2016ChgPct_Pop_ages_35_49_2000_16 = Age: Change, % Population ages 35-49, 2000-2016Pct_Pop_ages_50_64_2000 = Age: % Population ages 50-64, 2000Pct_Pop_ages_50_64_2016 = Age: % Population ages 50-64, 2016ChgPct_Pop_ages_50_64_2000_16 = Age: Change, % Population ages 50-64, 2000-2016Pct_Pop_ages_65over_2000 = Age: % Population ages 65 and over, 2000Pct_Pop_ages_65over_2016 = Age: % Population ages 65 and over, 2016ChgPct_Pop_ages_65over_2000_16 = Age: Change, % Population ages 65 and over, 2000-2016- - - - - -Race_Tot_Pop_2016 = Race/Ethnicity: # Total population, 2016Pct_NotHisp_White_2016 = Race/Ethnicity: % Not Hispanic, White alone, 2016Pct_NotHisp_White_2000 = Race/Ethnicity: % Not Hispanic, White alone, 2000ChgPct_NonHisp_White_2000_16 = Race/Ethnicity: Change, % Non-Hispanic White, 2000-2016Pct_NotHisp_Black_AA_2016 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016Pct_NotHisp_Black_AA_2000 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000ChgPct_NonHisp_Black_AA_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016Pct_NotHisp_AsianPac_2000 = Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000Pct_NonHisp_AsianPac_2016 = Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016ChgPct_NonHisp_AsianPac_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016Pct_NotHisp_Other_2000 = Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000Pct_NonHisp_Other_2016 = Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016ChgPct_NonHisp_Other_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Other, 2000-2016Pct_HispLat_any_2016 = Race/Ethnicity: % Hispanic or Latino (of any race), 2016Pct_HispLat_all_2000 = Race/Ethnicity: % Hispanic or Latino, all races, 2000ChgPct_HispLat_all_2000_16 = Race/Ethnicity: Change, % Hispanic or Latino all races, 2000-2016- - - - - -HealthIns_Tot_Pop_2016 = Health Insurance: # Total population, 2016Pop_wHealth_Insurance = Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016Pct_Pop_wHealth_Ins = Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016Pop_wPriv_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016Pct_Pop_wPriv_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016Population_with_public_coverage = Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016Pct_Pop_with_public_coverage = Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016Pop_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016Pct_Pop_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016Pop_u18_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pct_Pop_u18_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pop_18to64_Employed = Health Insurance: # Civilian population 18 to 64 years employed, 2016Pop_18to64_Empl_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016Pct_Pop_18to64_Emp_wNo_Hlth_Ins = Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016Pop_18to64_Unemployed = Health Insurance: # Civilian population 18 to 64 years unemployed, 2016Pop_18to64_Unemp_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016Pct_Pop_18to64_Unemp_No_HlthIns = Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016Pop_18to64_Not_in_Labor_Force = Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016Pop_18to64_Not_LabFor_NoHlthIns = Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016PctPop_18to64_NotLFor_NoHlthIns = Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016- - - - - -Income_Tot_Pop_2016 = Income: # Total population, 2016Income_Total_households = Income: # Total Households, 2016Household_inc_less_35k = Income: # Household income less than $35,000, 2016Pct_Household_inc_less_35k = Income: % Household income less than $35,000, 2016Household_inc_35k_75k = Income: # Household income $35,000 to $74,999, 2016Pct_Household_inc_35k_75k = Income: % Household income $35,000 to $74,999, 2016Household_inc_75k_200k = Income: # Household income $75,000 to $199,999, 2016Pct_Household_inc_75k_200k = Income: % Household income $75,000 to $199,999, 2016Household_inc_200k_more = Income: # Household income $200,000 or more, 2016Pct_Household_inc_200k_more = Income: % Household income $200,000 or more, 2016Median_household_Income = Income: Median household income, 2016Median_HH_Income_2000 = Income: Median Household Income, 2000Chg_Median_HH_income_2000_2016 = Income: Change, Median household income, 2000-2016Average_Per_capita_Income = Income: Per capita income (dollars), 2016Aggregate_HH_Income = Income: Aggregate household income, 2016Average_Household_Income = Income: Mean household income, 2016- - - - - -Poverty_Tot_Pop_2016 = Poverty: # Total population, 2016Pop_PovertyStatus_Determined = Poverty: # Population for whom poverty status determined, 2016Population_in_poverty = Poverty: # Population below poverty, 2016Percent_Population_in_poverty = Poverty: % Population below poverty, 2016Population_poverty_2000 = Poverty: # Population below poverty, 2000Pct_Pop_poverty_2000 = Poverty: % Population below poverty, 2000Chg_Pct_Pop_poverty_2000_2016 = Poverty: Change, % Population in poverty, 2000-2016Pop_under18_PovStatusDetermined = Poverty: # Population under 18 years for whom poverty status determined, 2016Pop_under18_in_Poverty = Poverty: # Population under 18 years below poverty, 2016Pct_Pop_under18_in_Poverty = Poverty: % Population under 18 years below poverty, 2016Pop_18_64_PovStatus_Determined = Poverty: # Population 18 to 64 years for whom poverty status determined, 2016Pop_18_64_Years_in_Poverty = Poverty: # Population 18 to 64 years below poverty, 2016Pct_Pop_18_64_Years_in_Poverty = Poverty: % Population 18 to 64 years below poverty, 2016Pop_65older_PovStatusDetermined = Poverty: # Population 65 years and over for whom poverty status determined, 2016Pop_65older_in_Poverty = Poverty: # Population 65 years and over below poverty, 2016Pct_Pop_65older_in_Poverty = Poverty: % Population 65 years and over below poverty, 2016- - - - - -Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016For additional information, please visit the Atlanta Regional Commission atwww.atlantaregional.com.
Copyright Text: U.S. Census Bureau, Atlanta Regional Commission
NAME
(
type: esriFieldTypeString, alias: NAME, length: 100
)
HealthIns_Tot_Pop_2016
(
type: esriFieldTypeDouble, alias: Health Insurance: # Total population, 2016
)
Pop_wHealth_Insurance
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016
)
Pct_Pop_wHealth_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016
)
Pop_wPriv_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016
)
Pct_Pop_wPriv_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016
)
Population_with_public_coverage
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016
)
Pct_Pop_with_public_coverage
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016
)
Pop_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016
)
Pct_Pop_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016
)
Pop_u18_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016
)
Pct_Pop_u18_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016
)
Pop_18to64_Employed
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years employed, 2016
)
Pop_18to64_Empl_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016
)
Pct_Pop_18to64_Emp_wNo_Hlth_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016
)
Pop_18to64_Unemployed
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years unemployed, 2016
)
Pop_18to64_Unemp_wNo_Health_Ins
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016
)
Pct_Pop_18to64_Unemp_No_HlthIns
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016
)
Pop_18to64_Not_in_Labor_Force
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016
)
Pop_18to64_Not_LabFor_NoHlthIns
(
type: esriFieldTypeDouble, alias: Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016
)
PctPop_18to64_NotLFor_NoHlthIns
(
type: esriFieldTypeDouble, alias: Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016
)
Description: This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show various demographic data by census tract in the state of Georgia. This subset includes the following categories which were deemed especially relevant to the 500 Cities health data project as determinants of health outcomes: age, race/ethnicity, income, health insurance, and poverty.The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.Base Attributes:GEOID10 = 2010 Census tract identifier (combination of FIPS codes for state, county, and tract)NAME = 2010 Census tract number and county name- - - - - -Attributes from ACS:Age_Tot_Pop_2016 = Age: # Total population, 2016Pct_Pop_und_age_5_2000 = Age: % Population under age 5, 2000Pct_Pop_und_age_5_2016 = Age: % Population under age 5, 2016ChgPct_Pop_und_age_5_2000_16 = Age: Change, % Population under age 5, 2000-2016Pct_Pop_und_18_2000 = Age: % Population under age 18, 2000Pct_Pop_und_18_2016 = Age: % Population under age 18, 2016ChgPct_Pop_und_18_2000_16 = Age: Change, % Population under age 18, 2000-2016Pct_Pop_ages_18_34_2000 = Age: % Population ages 18-34, 2000Pct_Pop_ages_18_34_2016 = Age: % Population ages 18-34, 2016ChgPct_Pop_ages_18_34_2000_16 = Age: Change, % Population ages 18-34, 2000-2016Pct_Pop_ages_35_49_2000 = Age: % Population ages 35-49, 2000Pct_Pop_ages_35_49_2016 = Age: % Population ages 35-49, 2016ChgPct_Pop_ages_35_49_2000_16 = Age: Change, % Population ages 35-49, 2000-2016Pct_Pop_ages_50_64_2000 = Age: % Population ages 50-64, 2000Pct_Pop_ages_50_64_2016 = Age: % Population ages 50-64, 2016ChgPct_Pop_ages_50_64_2000_16 = Age: Change, % Population ages 50-64, 2000-2016Pct_Pop_ages_65over_2000 = Age: % Population ages 65 and over, 2000Pct_Pop_ages_65over_2016 = Age: % Population ages 65 and over, 2016ChgPct_Pop_ages_65over_2000_16 = Age: Change, % Population ages 65 and over, 2000-2016- - - - - -Race_Tot_Pop_2016 = Race/Ethnicity: # Total population, 2016Pct_NotHisp_White_2016 = Race/Ethnicity: % Not Hispanic, White alone, 2016Pct_NotHisp_White_2000 = Race/Ethnicity: % Not Hispanic, White alone, 2000ChgPct_NonHisp_White_2000_16 = Race/Ethnicity: Change, % Non-Hispanic White, 2000-2016Pct_NotHisp_Black_AA_2016 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016Pct_NotHisp_Black_AA_2000 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000ChgPct_NonHisp_Black_AA_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016Pct_NotHisp_AsianPac_2000 = Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000Pct_NonHisp_AsianPac_2016 = Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016ChgPct_NonHisp_AsianPac_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016Pct_NotHisp_Other_2000 = Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000Pct_NonHisp_Other_2016 = Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016ChgPct_NonHisp_Other_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Other, 2000-2016Pct_HispLat_any_2016 = Race/Ethnicity: % Hispanic or Latino (of any race), 2016Pct_HispLat_all_2000 = Race/Ethnicity: % Hispanic or Latino, all races, 2000ChgPct_HispLat_all_2000_16 = Race/Ethnicity: Change, % Hispanic or Latino all races, 2000-2016- - - - - -HealthIns_Tot_Pop_2016 = Health Insurance: # Total population, 2016Pop_wHealth_Insurance = Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016Pct_Pop_wHealth_Ins = Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016Pop_wPriv_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016Pct_Pop_wPriv_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016Population_with_public_coverage = Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016Pct_Pop_with_public_coverage = Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016Pop_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016Pct_Pop_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016Pop_u18_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pct_Pop_u18_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pop_18to64_Employed = Health Insurance: # Civilian population 18 to 64 years employed, 2016Pop_18to64_Empl_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016Pct_Pop_18to64_Emp_wNo_Hlth_Ins = Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016Pop_18to64_Unemployed = Health Insurance: # Civilian population 18 to 64 years unemployed, 2016Pop_18to64_Unemp_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016Pct_Pop_18to64_Unemp_No_HlthIns = Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016Pop_18to64_Not_in_Labor_Force = Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016Pop_18to64_Not_LabFor_NoHlthIns = Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016PctPop_18to64_NotLFor_NoHlthIns = Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016- - - - - -Income_Tot_Pop_2016 = Income: # Total population, 2016Income_Total_households = Income: # Total Households, 2016Household_inc_less_35k = Income: # Household income less than $35,000, 2016Pct_Household_inc_less_35k = Income: % Household income less than $35,000, 2016Household_inc_35k_75k = Income: # Household income $35,000 to $74,999, 2016Pct_Household_inc_35k_75k = Income: % Household income $35,000 to $74,999, 2016Household_inc_75k_200k = Income: # Household income $75,000 to $199,999, 2016Pct_Household_inc_75k_200k = Income: % Household income $75,000 to $199,999, 2016Household_inc_200k_more = Income: # Household income $200,000 or more, 2016Pct_Household_inc_200k_more = Income: % Household income $200,000 or more, 2016Median_household_Income = Income: Median household income, 2016Median_HH_Income_2000 = Income: Median Household Income, 2000Chg_Median_HH_income_2000_2016 = Income: Change, Median household income, 2000-2016Average_Per_capita_Income = Income: Per capita income (dollars), 2016Aggregate_HH_Income = Income: Aggregate household income, 2016Average_Household_Income = Income: Mean household income, 2016- - - - - -Poverty_Tot_Pop_2016 = Poverty: # Total population, 2016Pop_PovertyStatus_Determined = Poverty: # Population for whom poverty status determined, 2016Population_in_poverty = Poverty: # Population below poverty, 2016Percent_Population_in_poverty = Poverty: % Population below poverty, 2016Population_poverty_2000 = Poverty: # Population below poverty, 2000Pct_Pop_poverty_2000 = Poverty: % Population below poverty, 2000Chg_Pct_Pop_poverty_2000_2016 = Poverty: Change, % Population in poverty, 2000-2016Pop_under18_PovStatusDetermined = Poverty: # Population under 18 years for whom poverty status determined, 2016Pop_under18_in_Poverty = Poverty: # Population under 18 years below poverty, 2016Pct_Pop_under18_in_Poverty = Poverty: % Population under 18 years below poverty, 2016Pop_18_64_PovStatus_Determined = Poverty: # Population 18 to 64 years for whom poverty status determined, 2016Pop_18_64_Years_in_Poverty = Poverty: # Population 18 to 64 years below poverty, 2016Pct_Pop_18_64_Years_in_Poverty = Poverty: % Population 18 to 64 years below poverty, 2016Pop_65older_PovStatusDetermined = Poverty: # Population 65 years and over for whom poverty status determined, 2016Pop_65older_in_Poverty = Poverty: # Population 65 years and over below poverty, 2016Pct_Pop_65older_in_Poverty = Poverty: % Population 65 years and over below poverty, 2016- - - - - -Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016For additional information, please visit the Atlanta Regional Commission atwww.atlantaregional.com.
Copyright Text: U.S. Census Bureau, Atlanta Regional Commission
Description: This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2012-2016, to show various demographic data by census tract in the state of Georgia. This subset includes the following categories which were deemed especially relevant to the 500 Cities health data project as determinants of health outcomes: age, race/ethnicity, income, health insurance, and poverty.The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number. The Census Bureau also calculates a corresponding margin of error (MOE) for ACS measures (although margins of error are not included in this dataset).The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2012-2016). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.For further explanation of ACS estimates and margin of error, refer to Census Bureau documentation.Base Attributes:GEOID10 = 2010 Census tract identifier (combination of FIPS codes for state, county, and tract)NAME = 2010 Census tract number and county name- - - - - -Attributes from ACS:Age_Tot_Pop_2016 = Age: # Total population, 2016Pct_Pop_und_age_5_2000 = Age: % Population under age 5, 2000Pct_Pop_und_age_5_2016 = Age: % Population under age 5, 2016ChgPct_Pop_und_age_5_2000_16 = Age: Change, % Population under age 5, 2000-2016Pct_Pop_und_18_2000 = Age: % Population under age 18, 2000Pct_Pop_und_18_2016 = Age: % Population under age 18, 2016ChgPct_Pop_und_18_2000_16 = Age: Change, % Population under age 18, 2000-2016Pct_Pop_ages_18_34_2000 = Age: % Population ages 18-34, 2000Pct_Pop_ages_18_34_2016 = Age: % Population ages 18-34, 2016ChgPct_Pop_ages_18_34_2000_16 = Age: Change, % Population ages 18-34, 2000-2016Pct_Pop_ages_35_49_2000 = Age: % Population ages 35-49, 2000Pct_Pop_ages_35_49_2016 = Age: % Population ages 35-49, 2016ChgPct_Pop_ages_35_49_2000_16 = Age: Change, % Population ages 35-49, 2000-2016Pct_Pop_ages_50_64_2000 = Age: % Population ages 50-64, 2000Pct_Pop_ages_50_64_2016 = Age: % Population ages 50-64, 2016ChgPct_Pop_ages_50_64_2000_16 = Age: Change, % Population ages 50-64, 2000-2016Pct_Pop_ages_65over_2000 = Age: % Population ages 65 and over, 2000Pct_Pop_ages_65over_2016 = Age: % Population ages 65 and over, 2016ChgPct_Pop_ages_65over_2000_16 = Age: Change, % Population ages 65 and over, 2000-2016- - - - - -Race_Tot_Pop_2016 = Race/Ethnicity: # Total population, 2016Pct_NotHisp_White_2016 = Race/Ethnicity: % Not Hispanic, White alone, 2016Pct_NotHisp_White_2000 = Race/Ethnicity: % Not Hispanic, White alone, 2000ChgPct_NonHisp_White_2000_16 = Race/Ethnicity: Change, % Non-Hispanic White, 2000-2016Pct_NotHisp_Black_AA_2016 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2016Pct_NotHisp_Black_AA_2000 = Race/Ethnicity: % Not Hispanic, Black or African American alone, 2000ChgPct_NonHisp_Black_AA_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Black or African-American, 2000-2016Pct_NotHisp_AsianPac_2000 = Race/Ethnicity: % Not Hispanic, Asian or Pacific Islander alone, 2000Pct_NonHisp_AsianPac_2016 = Race/Ethnicity: % Non-Hispanic Asian or Pacific Islander, 2016ChgPct_NonHisp_AsianPac_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Asian or Pacific Islander, 2000-2016Pct_NotHisp_Other_2000 = Race/Ethnicity: % Not Hispanic, other (Native American, other race, two or more races), 2000Pct_NonHisp_Other_2016 = Race/Ethnicity: % Non-Hispanic other (Native American, other one race, two or more races), 2016ChgPct_NonHisp_Other_2000_16 = Race/Ethnicity: Change, % Non-Hispanic Other, 2000-2016Pct_HispLat_any_2016 = Race/Ethnicity: % Hispanic or Latino (of any race), 2016Pct_HispLat_all_2000 = Race/Ethnicity: % Hispanic or Latino, all races, 2000ChgPct_HispLat_all_2000_16 = Race/Ethnicity: Change, % Hispanic or Latino all races, 2000-2016- - - - - -HealthIns_Tot_Pop_2016 = Health Insurance: # Total population, 2016Pop_wHealth_Insurance = Health Insurance: # Civilian noninstitutionalized population w/ health insurance, 2016Pct_Pop_wHealth_Ins = Health Insurance: % Civilian noninstitutionalized population w/ health insurance, 2016Pop_wPriv_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ private health insurance, 2016Pct_Pop_wPriv_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ private health insurance, 2016Population_with_public_coverage = Health Insurance: # Civilian noninstitutionalized population w/ public health insurance, 2016Pct_Pop_with_public_coverage = Health Insurance: % Civilian noninstitutionalized population w/ public health insurance, 2016Pop_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population w/ no health insurance, 2016Pct_Pop_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population w/ no health insurance, 2016Pop_u18_wNo_Health_Ins = Health Insurance: # Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pct_Pop_u18_wNo_Health_Ins = Health Insurance: % Civilian noninstitutionalized population under 18 w/ no health insurance, 2016Pop_18to64_Employed = Health Insurance: # Civilian population 18 to 64 years employed, 2016Pop_18to64_Empl_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years employed, no health insurance, 2016Pct_Pop_18to64_Emp_wNo_Hlth_Ins = Health Insurance: % Civilian population 18 to 64 years employed, no health insurance, 2016Pop_18to64_Unemployed = Health Insurance: # Civilian population 18 to 64 years unemployed, 2016Pop_18to64_Unemp_wNo_Health_Ins = Health Insurance: # Civilian population 18 to 64 years unemployed, no health insurance, 2016Pct_Pop_18to64_Unemp_No_HlthIns = Health Insurance: % Civilian population 18 to 64 years unemployed, no health insurance, 2016Pop_18to64_Not_in_Labor_Force = Health Insurance: # Civilian population 18 to 64 years not in labor force, 2016Pop_18to64_Not_LabFor_NoHlthIns = Health Insurance: # Civilian population 18 to 64 years not in labor force, no health insurance, 2016PctPop_18to64_NotLFor_NoHlthIns = Health Insurance: % Civilian population 18 to 64 years not in labor force, no health insurance, 2016- - - - - -Income_Tot_Pop_2016 = Income: # Total population, 2016Income_Total_households = Income: # Total Households, 2016Household_inc_less_35k = Income: # Household income less than $35,000, 2016Pct_Household_inc_less_35k = Income: % Household income less than $35,000, 2016Household_inc_35k_75k = Income: # Household income $35,000 to $74,999, 2016Pct_Household_inc_35k_75k = Income: % Household income $35,000 to $74,999, 2016Household_inc_75k_200k = Income: # Household income $75,000 to $199,999, 2016Pct_Household_inc_75k_200k = Income: % Household income $75,000 to $199,999, 2016Household_inc_200k_more = Income: # Household income $200,000 or more, 2016Pct_Household_inc_200k_more = Income: % Household income $200,000 or more, 2016Median_household_Income = Income: Median household income, 2016Median_HH_Income_2000 = Income: Median Household Income, 2000Chg_Median_HH_income_2000_2016 = Income: Change, Median household income, 2000-2016Average_Per_capita_Income = Income: Per capita income (dollars), 2016Aggregate_HH_Income = Income: Aggregate household income, 2016Average_Household_Income = Income: Mean household income, 2016- - - - - -Poverty_Tot_Pop_2016 = Poverty: # Total population, 2016Pop_PovertyStatus_Determined = Poverty: # Population for whom poverty status determined, 2016Population_in_poverty = Poverty: # Population below poverty, 2016Percent_Population_in_poverty = Poverty: % Population below poverty, 2016Population_poverty_2000 = Poverty: # Population below poverty, 2000Pct_Pop_poverty_2000 = Poverty: % Population below poverty, 2000Chg_Pct_Pop_poverty_2000_2016 = Poverty: Change, % Population in poverty, 2000-2016Pop_under18_PovStatusDetermined = Poverty: # Population under 18 years for whom poverty status determined, 2016Pop_under18_in_Poverty = Poverty: # Population under 18 years below poverty, 2016Pct_Pop_under18_in_Poverty = Poverty: % Population under 18 years below poverty, 2016Pop_18_64_PovStatus_Determined = Poverty: # Population 18 to 64 years for whom poverty status determined, 2016Pop_18_64_Years_in_Poverty = Poverty: # Population 18 to 64 years below poverty, 2016Pct_Pop_18_64_Years_in_Poverty = Poverty: % Population 18 to 64 years below poverty, 2016Pop_65older_PovStatusDetermined = Poverty: # Population 65 years and over for whom poverty status determined, 2016Pop_65older_in_Poverty = Poverty: # Population 65 years and over below poverty, 2016Pct_Pop_65older_in_Poverty = Poverty: % Population 65 years and over below poverty, 2016- - - - - -Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2012-2016For additional information, please visit the Atlanta Regional Commission atwww.atlantaregional.com.
Copyright Text: U.S. Census Bureau, Atlanta Regional Commission