Two Georgias:
Rural-Urban Disparities
in Health Behaviors and Outcomes
By Mary Eleanor Wickersham
For Healthcare Georgia Foundation
August 2014
Introduction
In southwest Georgia’s Stewart County, chronically unemployed residents gather
at the abandoned gas station in Lumpkin to drink beer, smoke marijuana, and talk,
something they have been doing for more than a decade as hope of steady work has
long since faded. The closest grocery store is ten miles from Lumpkin. “You have to go
somewhere else to get anything,” says Jill Walker, a former Stewart-Webster Hospital
employee who now works at the EMS in Lumpkin. Nearly 46% of residents are in
poverty in a county where a third of the population lacks a high school diploma, fewer
than half are in the labor force (U.S. Census), over 17% of women and 16% of men have
diagnosed diabetes (CDC Diabetes Interactive Atlas), and 22% are uninsured (U.S.
Census).
Much of the healthcare in the county is delivered through Stewart-Webster
Rural Health Clinic, a Federally Qualified Health Center, which has been a mainstay for
residents since the Richland hospital closed. Walker says that the cash-strapped county
has to heavily subsidize ambulance operations, since “most people don’t have any way
to pay.” Depending on the patient’s status, the EMS takes patients to Cuthbert,
Americus, Columbus, or Albany. Even after the 20 to 40 minutes required to reach the
patient, “Columbus is at least 45 minutes away, and Albany is even further,” she
explains, requiring travel time that takes one of the county’s two ambulances out of
operation for three or more hours. Heavy rains sometimes limit access to services for
poor residents on dirt roads that are prevalent in the north Lumpkin community of
Union. In Stewart County’s tiny Omaha community, a prime example of “you can’t get
there from here,” residents must drive west to cross the Chattahoochee River into
Alabama and then back east over the river again into Georgia to access the shortest
route to medical care in Columbus.
When Tri-County Health Care closed the doors of its Community Health Center in
Crawfordville in 2013, residents of Taliaferro County mourned the final loss of local
health care. Though Wilkes County’s Emergency Medical Service (EMS) transports
Taliaferro residents to Wills Memorial Hospital – one of Georgia’s 15 or more rural, at2
risk hospitals – the trip to the heart of Crawfordville requires a minimum of 20 minutes.
“If the ambulance has to get to the southern part of the county, it’s at least 40 minutes
one-way,” says Crawfordville Mayor Herrman Milner. The closest medical care is in
Warrenton at the Federally Qualified Health Center, though some residents drive
further to Greensboro, Washington, or Thomson.
These communities are not the only ones where health is affected by rurality,
though Stewart and Taliaferro are among the most remote and poorest counties in the
state. In Clay County, on the Alabama line in southwest Georgia, County Health Rankings
reports residents’ 19,239/100,000 “years of potential life lost,” i a startlingly high
measure of premature death in comparison to the state rate of 7,697/100,000. In
Warren County, in east-middle Georgia, 36.3% of residents self-report poor or fair
health, a proportion four times higher than for the state as a whole (County Health
Rankings).
Ironically, rural residents in the U.S. were long considered healthier than their
urban counterparts, a trend which began changing in the 1980s (Cossman et al. 2010,
1418). The list of contributing causes for the shift is long: lack of access to health care;
distance to a hospital; greater poverty; out-migration of healthier, younger people due
to lack of jobs, thereby leaving an older and less healthy population in place; lower
educational attainment; cultural variation that influences personal behaviors and risktaking; higher rates of obesity; lower use of health resources; and less aggressive or
outdated treatment, among others. The Wall Street Journal, citing the disparate
outcomes, points out that nationally, “About 25% of the population lives in rural areas,
but they are served by only 10% of the country’s physicians” (Beck 2011).
Substantial research over the last two decades confirms disparities in urban-rural
health outcomes and behaviors, especially when rural and inner city areas are
contrasted with suburban areas (Ingram and Franco 2014; Singh and Siahpush 2013;
Zeng, You, Mills, Alwang, Royster, Studer, and Dwamena 2012; Cossman, James, Cosby,
and Cossman 2010; Eberhardt and Pamuk 2004). Ingram and Franco (2014) report the
following findings using data from 2008 to 2010:
3
•
•
•
•
•
•
The death rate for all population sectors is lowest in the suburbs and highest in
the most rural counties.
The death rate from motor vehicle accidents escalates as counties become more
rural.
Cerebrovascular disease rates are lowest in the suburbs, increasing with
decreasing urbanization.
The proportion of residents who have self-described poor or fair health status is
highest in inner cities and the most rural counties.
Persons less likely to have health insurance are those who live in inner city and
more rural counties, both “micropolitan” counties and extremely rural counties.
The rate of smoking decreases with increasing urbanization.
The purpose of this paper is to examine health data from Georgia counties to
determine if there are patterns in health outcomes and behaviors that support current
research indicating that there is a “mortality penalty” (Cossman et al. 2010, 1418) or
even a “morbidity penalty” for rural residents in Georgia, when compared to their more
urban neighbors. Such an analysis is important for those interested in public health,
according to Singh and Siahpush, because it “provides important insights into the role of
health-policy interventions and of behavioral and healthcare factors such as smoking,
obesity, physical activity, and differential access to health services, as well as of
changing socioeconomic conditions . . . [and] important for allocating critical social and
public health resources towards those in rural or urban areas who may be at higher risk
of mortality from major chronic conditions and injuries” (2013, 273).
Methodology
One of the challenges of exploring the variation in health behaviors and
outcomes by geographic location is the lack of a standard definition of rural.
“Unfortunately, no single definition of rural exists or is commonly used,” according to
Klugman and Dalinis (2008, 2). Georgia law defines counties with a population of less
than 35,000 as rural (O.C.G.A. § 31-6-2(32)), thereby classifying 108 counties as rural
under the state definition. The U.S. Office of Rural Health Policy (ORHP) of the Health
Resources Services Administration and the federal Office of Management and Budget
delineate as rural 85 counties not designated “metropolitan” or in a metropolitan
4
statistical area by the U.S. Census. The same 85 Georgia counties are also delineated as
rural by the U.S. Department of Agriculture Economic Research Service, which uses a
continuum of categories to further differentiate the most urban from the most rural.
This paper adopts the use of the 85 non-metropolitan areas, categories 4 – 9 in
the Economic Research Service list, as rural counties. This delineation alone, however,
does not adequately describe counties like Twiggs, McIntosh, Quitman, Marion,
Chattahoochee, and others that are clearly rural, though described as metropolitan
because of their proximity to urban areas. When the State of Georgia definition of rural
provides more explanatory data about the topic, that information is also discussed.
Note that the Georgia Department of Public Health subscribes to the state definition.
The unit of analysis is in all cases the county. When comparisons are made
between rural and urban, the analysis explains the prevalence of the health factor or
outcome in counties by their locale. Data used for comparisons is the most recent
available and is collected from County Health Rankings, the Georgia Department of
Public Health Online Analytical Statistical Information System, U.S.D.A.’s Economic
Research Service, the U.S. Census, the Georgia Statistics System, and other publically
available data and academic literature as referenced. Note that when statistical analysis
uses the Cramer’s V test of significance, a Cramer’s V of .25 - .30 is moderately strong
and .30 - .35 is a very strong association.
Health Behaviors
Figure 1. Proportion of Smokers
in Counties by Locale
Cigarette Smoking
< 21%
“Tobacco use is the
single most preventable cause
100%
80%
United States,” according to
60%
Health and Human Services
organization that sets goals for
improving population health.
27% and >
p = .0002, Cramer's V = .26
of death and disease in the
Healthy People 2020, the U.S.
21% to <27%
40%
20%
0%
Metro (1 -3)
Non-Metro (4-6)
Non-Metro (7-9)
Note that the rate of smoking decreases with
urbanization.
5
The Surgeon General’s 2014 finding that “very large disparities in tobacco use remain
across groups defined by race, ethnicity, educational level, and socioeconomic status” is
confirmed in Georgia data (2014, 4). A higher proportion of rural Georgia residents
smoke cigarettes than do urban residents. Data on daily cigarette smoking indicates that
2
there is a negative linear correlation between cigarette smoking and size of county (r =
-.35), that is, the smaller the county population, the greater the prevalence of smoking.
Using the State of Georgia criteria for rurality, 25.6% of residents of rural counties
smoked cigarettes on a daily basis in 2012, compared to 22.5% of non-rural counties
(data from Dwyer-Lindgren, Mokdad, Srebotnjak, Flaxman, Hansen, and Murray 2014).
Of the 25 counties with the lowest rates of smoking in 2012, 23 were metropolitan
counties. Of the 25 counties with the highest rates of smoking, 18 are designated rural
by the U.S.D.A. formula, but 24 of the 25 have populations of fewer than 35,000, rural
under the State of Georgia definition.
Of counties with poverty
% Population That Quit Smoking
Figure 2. County Poverty Rates and
Percentage of Population That Quit Smoking
from 1996 to 2012
rates above the state mean,
75% are rural. These higher
r² = 0.3241
10
poverty rates are also
8
correlated with higher rates of
6
smoking (r2 = .31) and lower
4
rates of smoking cessation (See
2
Figure 2). Seven of the state’s
0
-2
0
20
40
60
% of Residents in Poverty by County
smallest rural and most
poverty-stricken counties
showed net increases in
As county poverty rates increase, the rate of smoking
cessation decreases.
smoking from 1996 to 2012.
Sexually Transmitted Diseases
Sexually transmitted diseases, although present in all counties, continue to be
primarily “an urban problem” (Raychowdhury, Tedders, Jones 2008, 1). There is not a
6
statistically significant difference in urban and rural rates for all STDs. About 30% of
variation in STD prevalence is, however, related to poverty.
Recently reported research indicates that the south has a higher number of HIV
cases than other regions of the country. Almost half of new cases in 2011 were in the
southern region of the U.S. with a higher proportion of fatalities (Reif, Safley, Wilson,
Whetten 2014, 1). HIV case rates, as reported by County Health Rankings, which omits
five of Georgia’s smallest counties, indicate that 38% of rural counties and 27% of urban
counties have HIV case rates above the state mean.
Drug and Alcohol
Figure 3. Retail Controlled Substances Purchases Per
Capita by County Locale, July 2013 - May 2014
Use
There is no
relationship
between binge
ii
drinking and
rurality in Georgia,
but data from the
Georgia Drug and
Narcotics Agency
indicates that
p = .008, Cramer's V = .25
80
60
40
20
0
Metro (1-3)
Non-Metro (4-6)
< 2.12 Per Capita
2.12 up to < 2.5/Per Capita
Non-Metro (7-9)
2.5 and >/Per Capita
The most rural counties have higher proportions of per capita retail
purchases of controlled substances from retail pharmacies.
controlled substance use may be a growing problem in rural areas. In Georgia, rural
counties have higher per capita retail purchases of controlled substances than do more
urban counties. (See Figure 3.) This Georgia data reflects a national trend of higher
opioid analgesic use in rural areas that may “lead to greater availability for nonmedical
use through diversion” (Keyes, Cerda, Brady, Havens, Galea 2014, e55). Some of the
effect may be due to the fact that more rural areas have more older residents with
higher demand for chronic pain remedies, but Keyes et al. (2014, e54) believe, “Adverse
economic conditions and high rates of unemployment may create greater vulnerability
to drug use” among young people in rural areas. It is noteworthy that of the 38 counties
7
with 2.5 controlled prescriptions per capita or higher, 84% have populations of less than
35,000. The state mean is 2.12 prescriptions per capita, and the range is from .68 to 3.8.
Teen Birth Rate
Although teen birth rates have declined in recent years, according to the CDC,
“geographic, socioeconomic, and racial and ethnic disparities persist.” In Georgia, 35%
of the variation in teen birth rates is associated with poverty. Of the 25 counties with
the highest teen birth rates, 84% have populations of less than 35,000.
Mortality
Geographic disparities have been noted by researchers Singh and Siahpush, who
report that the gap between rural and urban “all-cause mortality” widened between
1990 and 2009 in the U.S. and further predict that “the non-metropolitan–metropolitan
gap in all-cause mortality is expected to widen even further by 2020” (2013, 288). Their
research indicates that “unintentional injuries, CVD, COPD,iii and lung cancer accounted
for 70% of the overall rural-urban gap in mortality,” and that “[c]hronic diseases
associated with lifestyle factors such as CVD, respiratory diseases, lung and colorectal
cancers, diabetes, and kidney diseases are becoming increasingly important
determinants of excess mortality in rural areas and among the rural poor” (2013, 288).
Motor Vehicle Accidents
and Other Injuries
Research has
100%
consistently shown that
80%
“fatal crash incidence
density is more than two
times higher on rural than
urban roads” (Zwerling,
Asa, Choi, Sprince, Jones
2005). Using the most
recent County Health
Figure 4. All Injury Deaths/100,000 by Locale
p < .0001, Cramer's V = .35
60%
40%
20%
0%
Metro (1-3)
Non-metro (4-6)
< 50/100,000
50 - 80/100,000
Non-Metro (7-9)
> 80/100,000
As Georgia counties grow more rural, the proportion of deaths from
injury increases.
Rankings Data, with the state’s smallest counties omitted due to lack of data, the mean
motor vehicle death rate for rural counties was 26.2/100,000 compared to 20.4/100,000
8
for urban areas. The differences in the death rate from vehicle crashes is more striking
when the most urban counties (categories 1 and 2) and the most rural counties
(categories 7 – 9 for which data was available) are compared: 19.5 deaths/100,000
versus 28.8 deaths/100,000 from 2004-2010. Zwerling, et al. (2005) suggest that
increasing seat belt use, reducing high speed crashes, and improving emergency and
trauma care are critical to reducing vehicle mortality in rural areas. There is no
statistically significant relationship between alcohol-impaired driving deaths and county
size.
Unintentional Injuries
Figure 5. Mortality Rates, 1999-2010, for
Unintentional Injuries By Locale
The National Rural
Mean or < (52.6/100,000)
Health Association reports
that in the U.S., “Rural
residents are nearly twice as
likely to die from
unintentional injuries other
than motor vehicle accidents
than are urban residents.” In
Georgia, 76% of non-
> Mean (52.6/100,000)
p = <.0001, Cramer's V = .44
100%
80%
60%
40%
20%
0%
Metro (1-3)
Non-Metro (4-6)
Non-Metro (7-9)
Mortality rates increase for unintentional injuries as counties become
more rural.
metropolitan counties have
unintentional injury rates higher than the state’s mean, compared to 34% of urban
counties. Figure 5 illustrates the association of rurality with death from unintentional
injury.
Premature Deaths: Years of Potential Life Lost
“Years of potential life lost (YPPL),” a measure that quantifies premature and
often preventable deaths, indicates that on average, urban residents in Georgia have
8,355.9 “YPPL” as compared to 9,744.8 “YPPL” for rural residents (County Health
Rankings 2014). When the most urban residents (Category 1) are compared to the most
rural residents (Categories 7 – 9), the gap widens from 7,814.6 for metropolitan to
10,111.2 for the most rural counties. Of the top ten counties in measures of “length of
9
Figure 6. Life Expectancy
(LE) Changes for Women,
1985 - 2010:
Green = Net loss in LE
Grey = < 1 year gain LE
life,” nine of ten are
urban; of those in the
bottom rankings, eight
of ten are extremely
rural and the
remaining two are
small counties
adjacent to more
urban areas.
One notable
finding is the variation
in changes in life expectancy between men and women between 1985 and 2010 (data
from Wang, Schumacher, Levitz, Mokdad, and Murray 2013). On average, women
showed a net gain of 1.64 years compared to a net gain of 4.8 years for men. While
males have increased longevity in all counties, in 19 counties – 17 of them with
populations under 35,000 – life expectancy for women declined during the 15 year
period. (See Figure 6.) The data show no significant relationship between location and
gains for men. Of those counties where life expectancy decreased or gains were less
than one year, 27 of 42 are non-metro counties and nine others are low population
counties adjacent to more urban areas. Using the State of Georgia definition, 85% of
those counties with declines in female life expectancy are rural.
Morbidity
Disease rates are not always reliably determined with existing data, unless there
is a system of mandatory reporting. Two principal avenues for data collection on
morbidity are available: death reports and coded hospital discharges, but challenges
exist with both. In rural Georgia, the coroner is seldom a medical professional, creating
problems with reliance on “cause of death” determinations. Even when medical
professionals sign the death certificate, the doctor may not have the patient’s full
history and this may lead to inaccurate reporting (Schulz 2014, 32). Cancer deaths at
10
home may be attributed on the death certificate to respiratory distress or heart attack.
Discharge rates from hospitals are also somewhat unreliable because they are not allinclusive. Though these measures are inadequate, they are adopted here in order to
derive an overall picture of disease rates by county.
Self-Described Health Status
Figure 7. Degree of Self-Described
Poor/Fair Health by County Locale
Using the State of Georgia
Metro (1-3)
definition for rural, the mean
proportion of residents with poor
Non-Metro (4-9)
p = .007, Cramer's V = .27
100%
or fair health for urban counties
was 17%, while the mean for rural
counties was 20.5%. Of counties
reporting the highest levels of
poor or fair health, 84% have
50%
0%
< 15%
15% - < 24%
24% and >
As counties become more rural, there is an increasing
percentage of persons reporting poor or fair health.
fewer than 35,000 residents.
(Some of Georgia’s smallest counties have inadequate data for reliable reporting.)
Mental Health
The Georgia Department of Behavioral Health estimates prevalence of mental
illness at the same rates across urban and rural populations. This practice is in part
confirmed by County Health Rankings data that shows no significant difference in selfreported poor mental health days, although 2013 data on 22 small population counties
are missing. There are, however, potential differences in outcomes for those with
mental health diagnoses. Recent research confirms that rural areas are underserved
where mental health is concerned, due to fewer trained providers (Walker, Berry,
Citron, Fitzgerald, Rapaport, Stephens, and Druss 2014, 4), “inability to pay, a strong
social stigma associated with seeking MBH [mental and behavioral health] care, an
ingrained sense of self-reliance incongruent with care seeking, and transportation
barriers . . . ” (McDonald, Curtis-Schaeffer, Theiler, Howard 2014, 37). There is no
statistically significant relationship between suicide and locale, based on compressed
11
data, 1999-2010 from 134 counties described in the Centers for Disease Control and
Prevention “Wonder Database.”
Obesity
Figure 8. Proportion of Obese Residents
by County Locale
As Georgia counties become
more non-metropolitan, the
obesity rate increases, according
80%
to data from County Health
60%
Rankings. (See Figure 8.) All of
40%
the counties with obesity rates of
less than 25% are in metro
p=.0035, Cramer's V = .30
100%
20%
0%
Metro (1)
<30% Obese
Atlanta. Using the State of
Georgia definition, 77% of
counties with obesity rates of
rural, is also an important
> 30% Obese
p = < .0001, Cramer's V = .37
60%
40%
30% of the variation in obesity
20%
0%
Metro (1-3)
40% of the variation in the food
environment index, a County
Non-Metro (7-9)
Figure 9. Physical Inactivity Rates by
Metro, Non-Metro Counties
variable, accounting for nearly
rates in the state and more than
Non-Metro (4-6)
Chart 8 illustrates that more rural counties have higher proportions
of obese residents. Chart 9 explains that residents of rural counties
are more likely to be physically inactive.
30% or more are rural.
Poverty, both urban and
Metro (2-3)
< 25 Inactivity
25 - 30% Inactive
Non-Metro (4-9)
> 30% Inactive
Health Rankings measure of access to healthy foods and “food insecurity.” Physical
inactivity is, of course, a factor in obesity and is associated with 34% of the variation in
county obesity rates. Figure 9 illustrates County Health Rankings’ data describing
inactivity rates by county locale. Of the counties with the greatest access to exercise
opportunities, 72% are metropolitan; of those with the least access, 72% are nonmetropolitan.
12
Diabetes
The mean rate of diabetes in Georgia in 2012 was 12.43% (County Health
Rankings), significantly greater than the U.S. rate of 9.3% (American Diabetes
Association). County rates vary widely, according to the Centers for Disease Control
Diabetes Interactive Atlas. In 2011, of the 25 counties with the lowest prevalence of
diabetes, 88% were metropolitan; of those with the highest rates, 80% were nonmetropolitan. There is a statistically significant difference in diabetes rates between
urban and rural areas (p = .0002; Cramer’s V = .33). In 75% of rural counties, at least 12%
of residents are diabetic. Thirty-one percent of the variation in diabetes prevalence is
associated with obesity rates, and among women, nearly 41% of the variation is
diabetes is associated with the poverty rate.
Heart Disease
Despite declines in
Figure 10. Death Rates from Heart Disease by
County Locale, 2008 - 2010
Metro Counties (1-3)
coronary heart disease (CHD)
across the country, a
retrospective review of CHD
data from 1999 – 2009
determined that “CHD
mortality remained higher in
black people than in white
people, and, in the South, it
Non-Metro Counties (4-9)
p = .003, Cramer's V = .27
100%
80%
60%
40%
20%
0%
271 - < 350/100,000
350 - < 425/100,000
425 and > / 100,000
Higher rates of heart disease are associated with increasing
rurality.
remained higher in rural than in urban areas” (Kulshreshtha, Goyal, Dabhadkar, Beledar,
and Vaccarino 2014, 19). Data from 2008 – 2010 on deaths from heart disease gleaned
from the CDC’s Division for Heart Disease and Stroke Prevention: Interactive Atlas
indicates higher rates of CHD with increasing rurality. (See Figure 10.) There are no clear
relationships between hospitalizations for heart disease diagnoses of Medicare
beneficiaries by metro and non-metro counties.
13
Stroke
Figure 11. Degree of Prevalence of Death from
Stroke by County Locale, 2008 -2010 Data
The research
68 - < 90/100,000
finding that “greater
urbanization appears to
p = .0003, Cramer's V = .25
80%
lower stroke mortality .
60%
Higginbotham,
Kleindorfer, McClure,
Soliman, Howard
2012) is supported in
110 and >/100,000
100%
be associated with
. . .” (Howard, Mullen,
90 - < 110/100,000
40%
20%
0%
Metro (1-3)
Non-Metro (4-6)
Non-Metro (7-9)
Higher rates of death from stroke are associated with increasing
rurality.
Georgia data derived from the CDC’s Interactive Atlas of Heart Disease and Stroke. (See
Figure 11.) Of the 79 counties where death rates from stroke were above the state
mean, 79% had populations under 35,000. Worth noting is the fact that of those
counties with death rates above the state mean, 25 are defined as urban, but 17 of the
25 have populations under 35,000. This provides evidence that these low-population
counties on the fringes of urban centers may not have any of the benefits of their larger,
metropolitan neighbors and, in fact, may suffer some negative consequences because of
lack of health services that may not be economically feasible due to proximity to the
larger community.
Howard, et al. note that “non-metro” blacks have a much high mortality rate and
that these “differences in incidence and survival following stroke [between rural whites
and rural blacks] may be related to control of vascular risk factors and access to care . .
.” (2012). Of those counties with high hospitalization rates for Medicare patients for
stroke-related codes, 76% were counties under 35,000. There is a small but statistically
significant relationship between hypertension and rurality in Georgia counties.
14
Cancers
Figure 12. Crude Cancer Rates/100,000 by Urban vs.
Rural Counties (RUCA Codes), 2004 - 2008, Georgia
Cancer Registry
Data from the
National Cancer
Leukemia
Institute indicates
Lymphoma
that, while progress is
Brain and Other Nervous System
being made in
Urinary System
Male Genital System
stabilizing and even
Female Genital System
reducing deaths from
many forms of cancer,
Breast
Skin, Excluding Basal and Squamous
Lung and Bronchus
more rural than urban
counties have higher
mortality rates from
Colon and Rectum
Digestive System
Oral Cavity and Pharynx
0
all cancers. Of
50
Urban
Georgia’s counties
100
150
200
Rural
with the highest rates of death from cancer, 24 of 25 are counties with populations
below 35, 000; 64% of the counties with the lowest cancer rates are metropolitan.
Low Birth Weight Babies
Of the 25 counties with the lowest rates of low birth weight babies, 76% are
metropolitan. Of the counties with the highest rates of low birth weights, 64% are rural.
Perhaps more important than locale is poverty: 33% of low birth weight prevalence in
counties is associated with poverty.
Lung Disease
Figure 13. Hospital Respiratory Discharge
Rates by County Locale
Data from the American
Below State Mean
Lung Association shows little
variation across counties in
Georgia for pediatric and adult
asthma, chronic bronchitis, and
emphysema, however, data from
the Georgia Department of Public
100%
Above State Mean
p = < . 0001, Cramer's V = .47
50%
0%
Metro (1-3)
Non-Metro (4-6)
Non-Metro (7-9)
Prevalence of respiratory diseases increases with rurality.
15
Health Online Statistical Analysis System indicates increasing hospital discharge rates for
all respiratory diseases with decreasing urbanization. This may reflect on inadequacy of
treatment rather than incidence in the population.
Kidney Disease
There are no significant relationships between county size and morbidity and
mortality as related to kidney disease.
Discussion
Evidence indicates that rurality impacts health status, but geographic location is
not the only variable to be considered in analyzing the disparities in health status by
county across Georgia. Researchers studying colorectal cancer in Georgia point out that
socio-economic status “often has a gradient effect on health,” and that “[a] challenge in
studying the association between rurality and health is being able to disentangle the
confounding effect of SES [socioeconomic status] associated with geographic residency”
(Hines, Markossian, Johnson, Dong, Bayakly 2014, e65).
In many rural areas, Georgians have been left behind health-wise due to factors
described as the “social determinants of health,” a combination of elements beyond the
individual’s own health decisions that affect health outcomes. These social
determinants include low educational attainment, lack of insurance, unemployment,
high poverty, lack of health resources, and longstanding cultural practices, which may
include culturally acceptable risk-taking behaviors. Braveman and Gottleib cite studies
that suggest that “medical care” may be associated with as little as “10%-15% of
preventable mortality,” (2014, 20) the remainder of outcomes due to social factors and
behaviors. Addressing change is critical now because “links between social factors and
health often play out over decades or generations” (Braveman and Gottleib 2014, 27.)
Table 2 provides a snapshot of the wide variation in non-health factors at the
opposite ends of the health spectrum, as viewed through the lens of the top and bottom
ten ranked Georgia counties in County Health Rankings.
16
Table 1. Snapshot of Socioeconomic Differences in Counties Ranked by Health Status
Measures
Mean Total Population, 2006 - 2010
Proportion of Counties with Less than 35,000 Population
Mean Median Income, 2010
Mean Percentage Minority Population, 2006 – 1010
Mean Percentage of Population with Less than College
Education
Mean Percentage in Poverty
Mean Percentage Female-Headed Household
Teen Birth Rate (per 1000, teens 15 – 19)
Mean Percentage of Population Over 65
Mean Proportion of Population Receiving Food Stamps
Unemployment Rate
Mean Proportion with Severe Housing Problems
Mean Proportion of Children Receiving Free Lunch at
School
Ten Counties with
Highest Rankings
(County Health
Rankings)
232,521
2/10
$62,625.2
27.06%
65.67%
Ten Counties with
Lowest Rankings
(County Health
Rankings)
10,060
10/10
$29,310
55.1%
90.8%
11.88%
14.61%
28.9
9.71%
5.74%
7.8%
16.7%
30.7%
31.33%
30.69%
154.5
15.79%
27.45%
11%
14.2%
73.9%
Figure 14 provides another view of the health status of rural counties when
compared to more urban counties. This chart makes clear that more rural counties fall
into the bottom quintiles of
County Health Rankings.
Kulshreshtha et al. report that
Figure 14. Metro, Non-Metro Counties
by County Health Outcomes Rankings
Metro (1-3)
Non-Metro (4-9)
p = < .0001, Cramer's V = .44
rural areas “rank poorly on 21
of 23 selected population
health indicators, behaviors,
and risk factors” (2014, 20).
When co-morbidities are
Lowest Quintile
8
4th Quintile
3rd Quintile
2nd Quintile
Top Quintile
considered, the rural-urban
24
12
20
8
24
22
24
10
7
divide seems even wider. (Table 3 provides a series of maps that illustrate that many of
the same counties are consistently in the bottom 25 in outcomes.) The identification of
these disparities is critical because recognition of “[u]rban-rural differences provide[s]
opportunities for optimizing health-care resources and improving prevention targeting
17
areas of highest need” (Kulshreshtha et al. 2014, 20). Failure to address these disparities
may result in a continuing downward spiral of poor health and declining economies.
Table 3. Rural/Urban Counties with the Poorest Health Outcomes
State’s 25 most obese counties
25 counties with highest discharge
rates for kidney disease
Top 25 counties in “Years of Potential
Life Lost”
Counties with highest rates of
diabetes
Counties with highest rates of low
birth weight babies
Counties with highest death rates
from heart disease
Counties with highest rates of deaths
from cancer
Counties with highest teen birth rates
Worst overall outcomes measures
from County Health Rankings
18
In Pulaski County in the 1990s, several teens were killed at an intersection on a
remote rural road when two cars collided on a dark night. It was “common practice” in
rural Georgia, a parent of one of the surviving teens explained, to cut off one’s car lights
at rural intersections to see if anyone else was coming so as to avoid stopping. Many
rural areas in Georgia, especially those highest in poverty and lowest in educational
attainment, are on just such a collision course with the future because of the
unacceptable, but “common practices” that now exist and have for too long been
accepted as givens in the poorest and most rural counties. The warning signs are
present: higher rates of smoking; higher rates of obesity; higher prevalence of lung
disease; higher proportions of teen births; higher rates of stroke, heart disease, and
hypertension; higher rates of diabetes; and disproportionate controlled substance use.
There are indeed “two Georgias,” the urban and suburban counties where health care is
a given, and the rest of the state, where access is limited and outcomes are worse.
There are no easy solutions, but perhaps it is time, as one article describes it, to shine
the light on “the causes of the causes” (Cossman et al. 2014) of the disparities that
affect rural Georgians.
19
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23
Endnotes
i
This data is from the National Center for Health Statistics, which defines this measure of premature
death as: “years of potential life lost before age 75/100,000 population (age-adjusted).”
ii
Binge drinking, according to the CDC, “is a pattern of drinking that brings a person’s blood alcohol
concentration (BAC) to 0.08 grams percent or above. This typically happens when men consume 5 or
more drinks, and when women consume 4 or more drinks, in about 2 hours.”
iii
CVD is the acronym for cardiovascular disease; COPD is the acronym for chronic obstructive pulmonary
disease.
Appendix A
County
Population
Estimate
2013
RuralUrban
Continuum
Codes
Description of Rural Urban Continuum Codes
Appling County
18236
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Atkinson County
8375
9
Bacon County
11096
7
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Baker County
3451
3
Metro - Counties in metro areas of fewer than 250,000 population
Baldwin County
45720
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Banks County
18395
8
Barrow County
69367
1
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Metro - Counties in metro areas of 1 million population or more
Bartow County
100157
1
Metro - Counties in metro areas of 1 million population or more
Ben Hill County
17634
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Berrien County
19286
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Bibb County
155547
3
Metro - Counties in metro areas of fewer than 250,000 population
Bleckley County
13063
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Brantley County
18411
3
Metro - Counties in metro areas of fewer than 250,000 population
Brooks County
16243
3
Metro - Counties in metro areas of fewer than 250,000 population
Bryan County
30233
2
Metro - Counties in metro areas of 250,000 to 1 million population
Bulloch County
70217
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Burke County
23316
2
Metro - Counties in metro areas of 250,000 to 1 million population
Butts County
23655
1
Metro - Counties in metro areas of 1 million population or more
Calhoun County
6694
8
Camden County
50513
4
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Candler County
10998
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Carroll County
110527
1
Metro - Counties in metro areas of 1 million population or more
Catoosa County
63942
2
Metro - Counties in metro areas of 250,000 to 1 million population
Charlton County
12171
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Chatham County
265128
2
Metro - Counties in metro areas of 250,000 to 1 million population
Chattahoochee County
11267
2
Metro - Counties in metro areas of 250,000 to 1 million population
Chattooga County
26015
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Cherokee County
214346
1
Metro - Counties in metro areas of 1 million population or more
Clarke County
116714
3
Metro - Counties in metro areas of fewer than 250,000 population
24
Clay County
3183
9
Clayton County
259424
1
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Metro - Counties in metro areas of 1 million population or more
Clinch County
6798
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Cobb County
688078
1
Metro - Counties in metro areas of 1 million population or more
Coffee County
42356
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Colquitt County
45498
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Columbia County
124053
2
Metro - Counties in metro areas of 250,000 to 1 million population
Cook County
17212
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Coweta County
127317
1
Metro - Counties in metro areas of 1 million population or more
Crawford County
12630
3
Metro - Counties in metro areas of fewer than 250,000 population
Crisp County
23439
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Dade County
16633
2
Metro - Counties in metro areas of 250,000 to 1 million population
Dawson County
22330
1
Metro - Counties in metro areas of 1 million population or more
Decatur County
27842
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
DeKalb County
691893
1
Metro - Counties in metro areas of 1 million population or more
Dodge County
21796
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Dooly County
14918
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Dougherty County
94565
3
Metro - Counties in metro areas of fewer than 250,000 population
Douglas County
132403
1
Metro - Counties in metro areas of 1 million population or more
Early County
11008
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Echols County
4034
3
Metro - Counties in metro areas of fewer than 250,000 population
Effingham County
52250
2
Metro - Counties in metro areas of 250,000 to 1 million population
Elbert County
20166
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Emanuel County
22598
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Evans County
11000
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Fannin County
23682
8
Fayette County
106567
1
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Metro - Counties in metro areas of 1 million population or more
Floyd County
96317
3
Metro - Counties in metro areas of fewer than 250,000 population
Forsyth County
175511
1
Metro - Counties in metro areas of 1 million population or more
Franklin County
22084
8
Fulton County
920581
1
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Metro - Counties in metro areas of 1 million population or more
Gilmer County
28292
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Glascock County
3082
9
Glynn County
79626
3
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Metro - Counties in metro areas of fewer than 250,000 population
Gordon County
55186
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Grady County
25011
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Greene County
15994
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Gwinnett County
805321
1
Metro - Counties in metro areas of 1 million population or more
Habersham County
43041
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Hall County
179684
3
Metro - Counties in metro areas of fewer than 250,000 population
Hancock County
9429
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Haralson County
28780
1
Metro - Counties in metro areas of 1 million population or more
Harris County
32024
2
Metro - Counties in metro areas of 250,000 to 1 million population
Hart County
25213
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Heard County
11834
1
Metro - Counties in metro areas of 1 million population or more
Henry County
203922
1
Metro - Counties in metro areas of 1 million population or more
Houston County
139900
3
Metro - Counties in metro areas of fewer than 250,000 population
25
Irwin County
9538
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Jackson County
60485
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Jasper County
13900
1
Metro - Counties in metro areas of 1 million population or more
Jeff Davis County
15068
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Jefferson County
16930
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Jenkins County
8340
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Johnson County
9980
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Jones County
28669
3
Metro - Counties in metro areas of fewer than 250,000 population
Lamar County
18317
1
Metro - Counties in metro areas of 1 million population or more
Lanier County
10078
3
Metro - Counties in metro areas of fewer than 250,000 population
Laurens County
48434
5
Nonmetro - Urban population of 20,000 or more, not adjacent to a metro area
Lee County
28298
3
Metro - Counties in metro areas of fewer than 250,000 population
Liberty County
63453
3
Metro - Counties in metro areas of fewer than 250,000 population
Lincoln County
7996
2
Metro - Counties in metro areas of 250,000 to 1 million population
Long County
14464
3
Metro - Counties in metro areas of fewer than 250,000 population
Lowndes County
109233
3
Metro - Counties in metro areas of fewer than 250,000 population
Lumpkin County
29966
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Macon County
14740
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Madison County
28120
3
Metro - Counties in metro areas of fewer than 250,000 population
Marion County
8742
2
Metro - Counties in metro areas of 250,000 to 1 million population
McDuffie County
21875
2
Metro - Counties in metro areas of 250,000 to 1 million population
McIntosh County
14333
3
Metro - Counties in metro areas of fewer than 250,000 population
Meriwether County
21992
1
Metro - Counties in metro areas of 1 million population or more
Miller County
6125
8
Mitchell County
23498
6
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Monroe County
26424
3
Metro - Counties in metro areas of fewer than 250,000 population
Montgomery County
9123
9
Morgan County
17868
1
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Metro - Counties in metro areas of 1 million population or more
Murray County
39628
3
Metro - Counties in metro areas of fewer than 250,000 population
Muscogee County
189885
2
Metro - Counties in metro areas of 250,000 to 1 million population
Newton County
99958
1
Metro - Counties in metro areas of 1 million population or more
Oconee County
32808
3
Metro - Counties in metro areas of fewer than 250,000 population
Oglethorpe County
14899
3
Metro - Counties in metro areas of fewer than 250,000 population
Paulding County
142324
1
Metro - Counties in metro areas of 1 million population or more
Peach County
27695
3
Metro - Counties in metro areas of fewer than 250,000 population
Pickens County
29431
1
Metro - Counties in metro areas of 1 million population or more
Pierce County
18758
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Pike County
17869
1
Metro - Counties in metro areas of 1 million population or more
Polk County
41475
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Pulaski County
12010
3
Metro - Counties in metro areas of fewer than 250,000 population
Putnam County
21218
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Quitman County
2513
9
Rabun County
16276
7
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Randolph County
7719
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Richmond County
200549
2
Metro - Counties in metro areas of 250,000 to 1 million population
Rockdale County
85215
1
Metro - Counties in metro areas of 1 million population or more
Schley County
5010
8
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
26
Screven County
14593
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Seminole County
8729
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Spalding County
64073
1
Metro - Counties in metro areas of 1 million population or more
Stephens County
26175
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Stewart County
6058
8
Sumter County
32819
6
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Talbot County
6865
8
Taliaferro County
1717
8
Tattnall County
25520
6
Taylor County
8906
8
Telfair County
16500
7
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Terrell County
9315
3
Metro - Counties in metro areas of fewer than 250,000 population
Thomas County
44720
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Tift County
40118
5
Nonmetro - Urban population of 20,000 or more, not adjacent to a metro area
Toombs County
27223
7
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Towns County
10471
9
Treutlen County
6885
7
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Troup County
67044
4
Nonmetro - Urban population of 20,000 or more, adjacent to a metro area
Turner County
8930
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Twiggs County
9023
3
Metro - Counties in metro areas of fewer than 250,000 population
Union County
21356
9
Upson County
27153
6
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Walker County
68756
2
Metro - Counties in metro areas of 250,000 to 1 million population
Walton County
83768
1
Metro - Counties in metro areas of 1 million population or more
Ware County
36312
5
Nonmetro - Urban population of 20,000 or more, not adjacent to a metro area
Warren County
5834
8
Washington County
21187
7
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, not adjacent to a metro area
Wayne County
30099
6
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Webster County
2799
8
Wheeler County
7421
9
White County
27144
6
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Completely rural or less than 2,500 urban population, not adjacent
to a metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Whitfield County
102599
3
Metro - Counties in metro areas of fewer than 250,000 population
Wilcox County
9255
8
Wilkes County
10593
6
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Wilkinson County
9563
8
Worth County
21679
3
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Nonmetro - Urban population of 2,500 to 19,999, adjacent to a metro area
Nonmetro - Completely rural or less than 2,500 urban population, adjacent to a
metro area
Metro - Counties in metro areas of fewer than 250,000 population
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