The Social Costs of Horizontal Hydraulic Fracturing - Cumper

Running head: THE SOCIAL COSTS OF HORIZONTAL 1
The Social Costs of Horizontal Hydraulic Fracturing:
A Colorado Case Study
Stephanie Cumper, Tim Minotas, Mariah Urueta
Central Michigan University

THE SOCIAL COSTS OF HORIZONTAL 2
Abstract
Horizontal Hydraulic Fracturing has been scientifically proven to pose environmentally
detrimental; however, little research has been conducted concerning the impacts fracking
(Horizontal Hydraulic Fracturing - HHF) has on social conditions in communities near to drilling
wells. Within this study, six counties in Colorado were analyzed. Three of the counties have had
or currently are housing wells. Three counties have never had horizontal hydraulic fracturing
operations on their land. Social conditions in the community were operationalized as birth
defects, sexually transmitted infections and crimes. The research question formed that directed
this case study was: What impacts does horizontal hydraulic fracturing have on the social
conditions of Colorado? From that question, and upon researching formerly conducted studies,
the following hypothesis was developed: Horizontal hydraulic fracturing will have a negative
impact on social conditions in Colorado. Social conditions are defined as measurements of birth
defect rates, crime rates and sexually transmitted infection (STI) rates.
Keywords: horizontal hydraulic fracturing (fracking), Colorado, social conditions, birth
defects, sexually transmitted infections (STIs), crime

The Social Costs of Horizontal Hydraulic Fracturing:
A Colorado Case Study
The Obama Administration has been a large proponent of drilling shale in America.
Currently, new natural gas pipelines are being constructed and expanded to prepare for the
upcoming natural gas boom. In addition, more exporting sites are being created for LNG
(Liquefied Natural Gas) to support American’s new natural gas trade deals with Japan. Another
way the Obama Administration is supporting the production and extraction of natural gas is by
fast tracking the Trans Pacific Partnership (TPP).
The process of horizontal hydraulic fracturing, commonly referred to as “fracking,” has
been a controversial way of natural gas extraction in America and even worldwide. It is
important to first distinguish between the two different types of fracking. Vertical hydraulic
fracturing has been used for approximately 40 years in America, and there has not been many
public concerns raised with this type of extraction. A pipe is inserted a few hundred feet into the
ground, then the shale rock is fractured and natural gas is uplifted. Horizontal fracking has been
used approximately for only the past 15 years with debate as to how well it has been tested.
Horizontal fracking entails drilling a pipe 5-10,000 feet into the ground of a shale layer. Once it
reaches the shale layer, the pipe is forced to bend, and then continue horizontally into the shale
layer. The pipe is then blasted with a mixture of sand, rocks, and +596 chemicals at extremely
high pressures. This blast then fractures the shale rock, and uplifts the natural gas.
Those in favor of fracking in the United States align with the Obama Administration’s
narrative that extracting natural gas will produce more American jobs, decrease our dependence
on foreign energy sources, and be the bridge to renewable energy expansion in the United States.

Individuals in opposition of fracking, though, have many issues with the drilling on account of
groundwater contamination, crop and cattle failure, and other environmental damages.
Literature Review
Amongst the debate between the two sides, two months ago it was officially confirmed that four
states have had ground water contamination occur due to horizontal fracking. There have been
many studies regarding the large amount of freshwater that is used during fracking,
contamination among land bases and waterways, and impacting native wildlife. All of these
studies relate to the way different ecosystems interact and are sustained. There have been recent
studies, though, on the social impacts that horizontal hydraulic fracturing is having on
communities in the United States.
While horizontal hydraulic fracturing, which we will now refer to as just “fracking,” is
occurring in many states of the nation where shale is located, it is occurring in even more
localized communities. This is why Colorado will be the primary focus of the rest of the
narrative. Specifically, the counties Weld, La Plata and Garfield, which all have fracking, were
researched. Three previously conducted case studies proved valuable in the evaluation of social
conditions in La Plata County and Garfield County: the “La Plata County Impact Report,” the
“Health Impact Assessment for Battlement Mesa, Garfield County Colorado,” and the “Potential
Exposure-Related Human Health Effects of Oil and Gas Development.” As a control, three
counties without fracking were also evaluated. These three counties are Pueblo, Fremont and
Boulder.
In Colorado, there have been alternating crime rates. A suggested reason for these
fluctuations can be attributed to horizontal hydraulic fracturing. Violent crime rates seem to have
a direct correlation to horizontal hydraulic fracturing in Colorado communities. Violent crimes

include murder and non-negligible manslaughter, forcible rape and aggravated assault.
Additional sources of injury include traffic incidents, specifically due to oil and gas trucks
running off of the road in cases of accidents, equipment being too heavy, not tightly secured,
tired truck drivers, etc.
In Colorado, there have been observations of fluctuations in Sexually Transmitted
Infection and Human Immunodeficiency Virus rates as oil and gas “man camps” are established
in areas that are being fracked. This has been partly from an increase of men in the area (most oil
and gas workers are men). As these workers are imbedded into the local community, their
actions have consequences on said community’s socioeconomic conditions - some of which are
fluctuating STI/HIV rates. “In Weld County, Colorado where fracking is occurring, from 2008-
2012 there was a 1% increase in STI’s. In Garfield, Colorado where fracking is occurring, from
2008-2012 there was a 1% decrease in STI’s. In La Plata, Colorado where fracking is also
occurring, from 2008-2012 people of the community a 1% decrease in STI’s” (STI/HIV, 2014).
Other consequences related to “man camp” activities, such as the production and distribution of
new jobs going to strangers to the area, dangerous working conditions, traffic accidents and road
damage and increases in crimes (i.e., substance abuse, the sex trade and domestic violence) are
suggested in “Local Government Fracking Regulations: A Colorado Case Study.”
In relation to the research that has been conducted on the health impacts of fracking,
Colorado has also seen changes in the rates of birth defects in areas where fracking is occurring.
Providing further supportive evidence is a previously conducted case study that researched the
relationship between birth outcomes and fracking wells, titled: “Birth Outcomes and Maternal
Residential Proximity to Natural Gas Development in Rural Colorado.”

Based upon the sources gathered thus far, and the analysis of the correlations shown
between horizontal hydraulic fracturing and specific social conditions, the following hypothesis
has been constructed: Horizontal hydraulic fracturing will have a negative impact on social
conditions in Colorado. Social conditions are operationally defined as measurements of birth
defect rates, crime rates and sexually transmitted infection rates. This hypothesis was formed
after conducting preliminary research concerning on the question: What impacts does horizontal
hydraulic fracturing have on the social conditions of Colorado? Therefore, the research
conducted in the following study was prepared and analyzed with the intention of supporting or
rejecting the theory that horizontal hydraulic fracturing poses hazardous risks to the health of
neighboring community inhabitants.
Discussion
Theoretically, it can be argued that social conditions are more important considerations to
be knowledgeable of than environmental conditions. Validation of this stance can be attributed to
the reality of the matter that social conditions are more likely to present a transparent impact on
the lives of Americans. Environmental alterations, however, are more opaque in their occurrence,
and as such, they are not stressed as fervently as social impacts are.
Considering such hypothetical state of affairs, it is logical to conduct research with the
purpose of discovering whether or not there is statistical significance that expresses a positive
correlation between the presence of horizontal hydraulic fracturing wells and negative social
conditions in a community.
Case Studies
To support this theoretical scenario, which in all actuality could be reality, inquisitional
case studies have been conducted. The findings of these studies attributed to the creation of the

research questions that provided intent to this present study. The studies reviewed prior to the
actual accumulation of raw statistical data discuss the health profiles in geographical locations in
close proximity to horizontal hydraulic fracturing.
Cumulatively, the case studies evaluated provide significant evidence to support the
hypothesis that health impacts, such as sexually transmitted infection, birth defects and crimes
(murder, rape, assault, fatal traffic accidents), are inversely affected by an increase of fracking in
a nearby area. “Garfield County experienced a steady increase in Chlamydia rates for the period
2005-2008” (Health, Appendix C page 35), meanwhile “in Garfield County, Colorado, the
increased demand for extraction of natural gas was most apparent between 2003 and 2008”
(Witter, McKenzie, Towle, Stinson, Scott, Newman and Adgate, 2010, Appendix B page 4). This
data provided in a health impact report of Garfield County in relation to the presence of HHF,
supports the conclusion that increased HHF generates increased cases of STIs (Chlamydia, in
this case).
Additionally, “a recent health study completed by the Saccoman Institute reported that
children in Garfield County had an increased asthma rate” (Witter, Stinson, Sackett, Putter,
Kinney, Teitelbaum and Newman, 2008, 26), which can potentially be contributed to the air
pollutants released in the presence of fossil fuel extraction and combustion. Expanding upon the
health implications HHF has had in Garfield County, Colorado – an area with extreme amounts
of extraction drilling – are findings that state, “Colorado has a relatively higher percentage of
low weight births than the United States overall. Garfield County has consistently had lower
percentages of low weight births than Colorado state percentages. The percentage of low birth
rates in Garfield County, in 2005 was 6.8 percent, falling below the state percentage of 9.3
percent” (Witter et al., 2008, 26). Furthermore, in a cohort study performed in rural Colorado,

“an association between density and proximity of natural gas wells within a 10-mile radius of
maternal residence and prevalence of congenital heart defects and possibly neural tube defects”
(McKenzie, Guo, Witter, Savitz and Newman, 2014, 412) was observed. Overall, past studies
has presented evidence that supports a direct correlation between an increase in natural gas
extraction (i.e. HHF) and birth defects.
Alongside the accumulated evidence supporting ill health effects in Garfield County,
Colorado as a negative side effect of fracking, is a suggested correlation between fracking and
increased crime rates. “In the first few years of the fracking boom in western Colorado’s
Piceance Shale, the Garfield County Sheriff’s Department had to hire fifteen new deputies, and
total offenses per year increased from 100 to 600, with assaults, DUIs, and drug-related crimes
becoming especially problematic” (Minor, 2013, 80). And while much of the data in past
research studies evaluates Garfield County specifically, empirical generalization expands the
results from that one county to county with similar circumstances.
Lastly, the case study that provided the largest degree of incentive for the origination of
the researched hypothesis was “The Social Costs of Fracking,” a study performed in
Pennsylvania. The study came to frightful conclusions. Horizontal hydraulic fracturing
contributes to an increase in heavy-truck crashes in areas of close proximity. “Heavy-truck
crashes rose 7.2 percent in heavily fracked rural Pennsylvania counties (with at least one well for
every 15 square miles) but fell 12.4 in unfracked rural counties after fracking began in 2005”
(“The Social,” 2013, 2). Social disorder arrests are more common in areas with fracking present,
as “disorderly conduct arrests increased by 17.1 percent in heavily fracked rural counties,
compared to 12.7 percent in unfracked rural counties” (“The Social,” 2013, 2). And lastly,
fracking has a direct relationship to increased cases of sexually transmitted infections. “After

fracking, the average increase in Chlamydia and Gonorrhea cases was 62 percent greater in
heavily fracked rural counties than in unfracked rural counties” (“The Social,” 2013, 2). The
Pennsylvania case study provided the template for the research conducted in Colorado.
Within a La Plata Impact Report of CBM development in the county, there is
acknowledgement that “as a result of poor isolation of the coal zones in older wells and potential
methane seepage from additional development, increased public safety risks are anticipated to
occur in proportion to the number of additional CBM-related facilities. There would be a
potentially increased risk of methane seepage in soils and water wells, fires, and accidents with
increased CBM development” (La Plata, 2002, E-5). This statement accounts for the awareness
environmentally hazardous companies have concerning the health impacts their extraction
processes – this case is focusing on coalbed methane, which is a form of natural gas extracted
from coal deposits – have on the lives of individuals in neighboring communities.
Methodology
The attainment of secondary sources was the first stage in the process of conducting
research. The potential sources’ credibility and degree of reliability was deliberated before
ascertaining raw statistics from said source. Additionally, relevant case studies conducted in the
past were evaluated. This process was to support the chosen hypothesis, as well as lend
assistance in discerning the necessary steps to take throughout the researching procedure.
After the selection of sources was complete, the raw statistical data from each source was
compiled and inputted into the SPSS program. To provide for differences in population size, data
was obtained by a specific rate for each separate variable. Typically, the rate was by every
10,000 persons or by every 100,000 persons. And to include data from a lengthier time frame

without complicating the methodology, a mean was calculated for each variable. The years
analyzed ranged from 2002 to 2012.
Data
The data amassed supported the three operationalized measurements of social conditions.
Raw statistics were gathered on birth defect rates in each county, crimes rates in each county and
sexually transmitted infection rates in each county. Furthermore, each form of social condition
measurement provided numerous sub-types. The two additional variables presented in the dataset
are counties, which was granted the values of 1.00 for Boulder County, 2.00 for Fremont County,
3.00 for Garfield County, 4.00 for La Plata County, 5.00 for Pueblo County and 6.00 for Weld
County, and horizontal hydraulic fracturing, which was given the values of 1.00 for fracked and
2.00 for not fracked.
Birth Defect Rates The sub-types provided beneath the measurement of birth defect
rates are the following: anomalies of abdominal wall, anomalies of diaphragm (including
diaphragmatic hernia), anomalies of pulmonary artery, arm/hand limb reduction, cardiovascular
anomalies, central nervous system anomalies, chromosomal anomalies, cleft lip with/without
cleft palate, cleft palate without cleft lip, coarctation of aorta, congenital hydrocephalus without
spida bifida, congenital hypertrophic pyloric stenosis, eye anomalies, gastrointestinal anomalies,
genitourinary anomalies, hip dislocation/dysplasia, infantile cerebral palsy, major cardiovascular
anomalies, major congenital anomalies, major eye anomalies, major musculoskeletal anomalies,
musculoskeletal anomalies, orofacial anomalies, ostium secundum type atrial septal defect,
patent ductus arteriosus, polydactyl/syndactyly, reduction deformity, respiratory anomalies,
tracheosophageal fistula, esophageal atresia and stenosis, transposition of great vessels, trisomy
21 (Down Syndrome) and ventricular septal defect. These were all provided on the source from

which the statistics were obtained; however, nearly half of the available birth defects have been
excluded from the dataset due to inefficient data.
Using Birth Data Statistics provided by the Colorado Department of Public Health and
Environment – the existence of which is due to the initiative of the Colorado Responds to
Children with Special Needs organization implementing a statewide public health program for
monitoring and preventing birth defects and development disabilities – raw statistics were
gathered in specific Colorado counties (i.e. Boulder, Fremont, Garfield, La Plata, Pueblo and
Weld), between the years 2007 and 2011 for all races, ethnicities, ages and genders. This process
involved selected the desired county and then choosing a selected structural anomaly
classification, such as ‘anomalies of the abdominal wall.’ The output was selected to be
generated as a rate. This process was repeated for each county and for all included birth defect
sub-types.
Crime Rates The sub-types provided beneath the measurement of crime rates are the
following: murder and non-negligible manslaughter, forcible rape, aggravated assault and fatal
traffic accidents. The source also provided criminal activities such as arson and robbery,
however, the desired target variable was focused on negatively impacted health conditions, rather
than economics.
In order to collect crimes statistics, the United States Department of Justice: Federal
Bureau of Investigation’s Uniform Crime Data Tool was employed. To use this tool, the agencies
(i.e. the police departments within specific counties) were selected, as well as the variables (i.e.
murder and non-negligible manslaughter, aggravated assault and forcible rape). The selected
time frame was from the year 2002 to the year 2012. The generated tables provided a total

statistic for each year for each agency. To simply the data, a mean was obtained, and that is the
number that was inputted into SPSS.
The fatal traffic accidents were gathered using City Data. The statistics were provided on
graphs. All of the statistics were provided on a 100,000 per individual rate, and as with the other
sub-types of crime, an overall mean was calculated.
Sexually Transmitted Infection Rates The sub-types provided beneath the
measurement of sexually transmitted infection rates are the following: Chlamydia, Gonorrhea,
primary and secondary syphilis and newly diagnosed HIV disease. These are all of the STIs
available on the source from which data was gathered.
The STI rates were gathered using STI/HIV Five-Year Trend Tables provided by the
Colorado Department of Public Health and Environment. The trends were available from 2008 to
2012 for demographic information of populations with Chlamydia, Gonorrhea, Syphilis and the
Human Immunodeficiency Virus. The statistics accumulated from the tables were categorized as
the rate per 100,000 individuals. As they were provided from the years 2008 to 2012, the rates
were summed and divided by 5 to get the mean. The overall mean for each STI is what was
inputted into SPSS.
Statistical Test Inferences
With the accomplishment of entering the data into a dataset on the SPSS program, the
next step was to run statistical tests to analyze whether or not HHF poses a negative correlation
with communities’ social conditions. This process was initiated by introducing the dataset to
basic descriptive frequencies. Then, a regression and a curve fit were generated to more
specifically analyze the dataset.

Frequencies The distribution frequencies were run as a preliminary test, merely to ensure
that all of the raw statistics were inputted into the SPSS program correctly. They displayed
affirmative results (Appendix A, Tables A1-A5), and with the data successfully incorporated, the
actual tests to measure the significance were implemented.
RegressionTo determine the statistical significance of the relationship between
horizontal hydraulic fracturing and the social conditions of communities in close geographic
proximity, an Analysis of Variance (ANOVA) was ran. The purpose of running an ANOVA
regression is to attain inferences about the degrees of variability between dependent and
independent variables. The analysis regressions provide enable researchers to understand how a
dependent variable is altered by any one independent variable, while the other independent
variables are controlled. The Analysis of Variation specifically allows researchers to understand
the differences between group means and the associated procedures, determining whether the
means of multiple groups are equal or not.
Because the variables within this study were so complex, their analysis required such a
statistical test. The Analysis of Variance entered for this dataset provided results that rejected the
hypothesis that HHF negatively impacts social conditions in Colorado (Appendix B, Tables B1-
B4).
Curve Fit To effectively graph the material presented in the dataset, Curve Estimation
Models (or Curve Fits) were generated for the relationship between the independent variable
(horizontal hydraulic fracturing) and each dependent variable. The responding graphs have
various results: some present graphs that support the hypothesis, some that reject the hypothesis
and some display no relationship between HHF and social conditions (Appendix C, Tables C1-
C4).

Challenges
As with any venture undertaken, challenges in the completion of this research study did
arise. These presented themselves in the appearance of personal bias, the selection of sampling
populations, discerning the meaning behind – and credibility of – data from the secondary
sources and coming to term with the lack of crime rate statistics from Garfield County – as well
as deciding whether the specific areas uncounted for should be deemed not available or obtained
from a separate source.
Personal Bias Upon deciding to pursue research concerning this specific research
question, it was acknowledged that the researchers are strongly biased in their preference for the
resulting statistics. However, in order to ensure the least amount of bias in the research as
possible, all samples were randomly selected, as were the operationalized measurements and the
sub-types within them. Efforts were taken to recognize that credible research is independent of
bias and in order for this case study to be considered worthy of academic review, it should be
unbiased as possible.
Sampling Selection Difficulties did present themselves in the selection of samples.
Initially, the research was going to evaluate three states with HHF and three states without HHF,
and social conditions were operationalized into eight different measurements, including farm
failure rates and increased tax rates. Upon beginning the project, the grandeur of these standards
appeared overwhelming and time-consuming. Then there was the suggestion to imitate the
Pennsylvania case study on HHF. The original idea was to repeat the study in Pennsylvania;
however, as that intention lacked originality, it was decided that three counties in Colorado with
HHF and three counties in Colorado without HHF would have their social conditions analyzed.

Social conditions were restructured to include only three operationalized measurements: birth
defects, crimes and STIs.
Yet another issue with the sample selection chosen was presented when attempting to
obtain raw data for crime rates in the counties. The source applied segregated Colorado crimes
according to police departments, and the study separated Colorado crimes by county. Therefore,
it was necessary to match each police department from which data was collected to its
corresponding county. This was a lengthy process.
Secondary Sources As with all data obtained from secondary sources, there is a potential
margin of error that may present itself in relation to the data employed in this study. Secondary
sources are more unreliable than primary sources for varying factors, some of which are the lack
of knowledge about the techniques by which the data was originally collected and any potential
bias implemented into the data by the original researcher and accumulation practices.
Testing Some trouble also arose in the process of searching for the appropriate test/s to
run to best suit the provided data. As mentioned above, a regression was generated, as was a
curve fit. After some trial, error and renewed understanding of the data, it was concluded that
Somer’s D, nor Lambda, nor Chi Square were adequate tests. A regression, however, suitably
applied itself to all of the available data and succeeded in providing a statistical significance.
Although, this was not until the variables were properly entered into the regression formula.
Inaccessibility of Specific Data Unfortunately, due to unknown reasoning, crime rates
were not available for murder and non-negligible manslaughter, forcible rape or aggravated
assault in Garfield County by the selected source. In efforts to reduce skewed data, this data was
not acquired from a differing source. Thus, there is no recorded data for any of these three sub-
types within the crimes rates measurement.

Conclusions and Future Study
The research conducted generated the conclusion that the social conditions in Colorado
(i.e. birth defect rates, crime rates and STI rates) have not been negatively impacted by
horizontal hydraulic fracturing in nearly locations. This conclusion was produced when the
regression’s results portrayed little statistical significance. Thus, the hypothesis devised at the
onset of the research study is rejected.
These results are most likely inconclusive; as the testing was generated from secondary
sources, which were subject to bias and inaccuracy, and the scope of the research could have
been expanded to more definitively analyze the effects of fracking on the social conditions of
nearby communities.
Future studies should be conducted in order to either confirm or reject the conclusion
reached upon the completion of this study. Ideally, future studies would evaluate control and test
groups of more similar demographics. Perhaps, evaluate only rural or only urban locations and
ensure the populations of the areas are as similar as possible. Another idea is to study different
states or include more control and test counties in the research. Evaluate the social conditions in
ten counties with HHF instead of three, and likewise for counties without HHF.
Furthermore, future studies could operationalize social conditions with different variables.
This study used birth defect rates, crime rates and sexually transmitted infection rates. Therefore,
much of what was considered within this study dealt with the mental and physical health defects
of fracking on communities. However, if researchers gathered rates on farm failures, crop
failures, small business booms or crashes, increased taxes, etc., the economic factors subjected to
variation could be evaluated.

A theory future researchers could evaluate is whether the relocation of large corporations
into a community generates a negative impact on the community’s social conditions. This idea
amplifies the original concept being studied in this research – that horizontal hydraulic fracturing
has a negative impact on the social conditions of a community – and alters the scope of the
hypothesis to cover all invasive corporations. This theory could be an alternative explanation for
why or why not social conditions are negatively affected by fracking; albeit, in this study, there
was no statistically significance to represent that hypothesis. However, perhaps with additional
research, statistically significance will be identified.

References
Birth Data Statistics. Colorado Responds to Children with Special Needs (CRCSN), n.d. Web. 1
Mar. 2014.
City Data. Advameg, Inc., 2012. Web. 1 Mar. 2014.
La Plata County Impact Report. La Plata County, Oct. 2002. Web. 1 Mar. 2014.
McKenzie, Lisa, Ruixin Guo, Roxana Witter, David Savitz, and Lee Newman. "Birth Outcomes
and Maternal Residential Proximity to Natural Gas Development in Rural Colorado."
Environmental Health Perspectives (2014): 1-27. Web. 1 Mar. 2014.
Minor, Joel. Local Government Fracking Regulations: A Colorado Case Study. N.p., 2013.
Web. 1 Mar. 2014.
"STI/HIV Five Year Trend Tables for Colorado Counties." Colorado Department of Public
Health and Environment: Division of Disease Control and Environmental Epidemiology.
State of Colorado, 2014. Web. 1 Mar. 2014.
"The Social Costs of Fracking: A Pennsylvania Case Study." Food & Water Watch. Food &
Water Watch, Sept. 2013. Web. 1 Mar. 2014.
Uniform Crime Reporting Statistics. United States Department of Justice: Federal Bureau of
Investigation, 2012. Web. 1 Mar. 2014.
Witter, Roxana, Lisa McKenzie, Meredith Towle, Kaylan Stinson, Kenneth Scott, Lee Newman
and John Adgate. Health Impact Assessment for Battlement Mesa, Garfield County
Colorado. Colorado School of Public Heath, Sept. Web. 1 Mar. 2014.

Witter, Roxana, Kaylan Stinson, Holly Sackett, Stefanie Putter, Gregory Kinney, Daniel
Teitelbaum and Lee Newman. Potential Exposure-Related Human Health Effects of Oil
and Gas Development. Colorado School of Public Heath, Colorado State University, 15
Sept. 2008. Web. 1 Mar. 2014.

Appendix A
Frequency Distributions
The Frequency Distribution tests were conducted to ensure the raw statistics accumulated from
research was properly inputted into the SPSS program. As basic tables, the distributions display
that given the successfully implemented dataset, any future tests will have adequate materials to
work with.
The first table, Table A1, verifies that there are six counties being evaluated in the dataset:
Boulder, Fremont, Garfield, La Plata, Pueblo and Weld. Separately, each county accounts for
16.7 percent of the county variable.
The second table, Table A2, presents similar information for horizontal hydraulic
fracturing, merely stating that there are three fracked counties and three unfracked counties
present in the dataset.
The next three tables, Table A3, A4 and A5, provide examples of frequency distributions
for each of the three diverse operationalized measures of social conditions. Table A3 represents
birth defect rates, Table A4 represents crime rates and Table A5 represents sexually transmitted
infection rates. Table A3 has a frequency of 2 for 5.00 because two of the counties presented that
statistic. Table A5 contains a statistic missing from the system because aggravated assault data
was not available for Garfield County.

Table A1
Counties
Frequency Percent Valid Percent Cumulative
Percent
Valid
Boulder 1 16.7 16.7 16.7
Fremont 1 16.7 16.7 33.3
Garfeild 1 16.7 16.7 50.0
La Plata 1 16.7 16.7 66.7
Pueblo 1 16.7 16.7 83.3
Weld 1 16.7 16.7 100.0
Total 6 100.0 100.0
Table A2
Horizontal hydraulic fracturing
Percent
Valid
Fracked 3 50.0 50.0 50.0
Not fracked 3 50.0 50.0 100.0
Total 6 100.0 100.0

Table A3
Anomalies of abdominal wall
Percent
Valid
3.40 1 16.7 16.7 16.7
5.00 2 33.3 33.3 50.0
6.50 1 16.7 16.7 66.7
6.90 1 16.7 16.7 83.3
8.70 1 16.7 16.7 100.0
Total 6 100.0 100.0
Table A4
Aggravated assault
Percent
Valid
358.35 1 16.7 20.0 20.0
397.95 1 16.7 20.0 40.0
469.74 1 16.7 20.0 60.0
909.46 1 16.7 20.0 80.0
1346.11 1 16.7 20.0 100.0
Total 5 83.3 100.0
Missing System 1 16.7
Total 6 100.0

Table A5
Chlamydia
Percent
Valid
172.98 1 16.7 16.7 16.7
255.04 1 16.7 16.7 33.3
264.00 1 16.7 16.7 50.0
282.16 1 16.7 16.7 66.7
337.40 1 16.7 16.7 83.3
516.36 1 16.7 16.7 100.0
Total 6 100.0 100.0

Appendix B
Analysis of Variance: Regression
To analyze the actual statistical significance portrayed between the independent variable,
horizontal hydraulic fracturing, and the dependent variable, social conditions (i.e. aggravated
assault, Chlamydia, etc.) a regression analysis referred to as the Analysis of Variance (ANOVA)
was performed. This test compared the relationship between a dependent variable with that of an
independent variable, while the other independent variable was controlled. The dependent
variable under which all dependent variables are grouped in this specific test is aggravated
assault. This is represented in Table B1.
In Table B2, there are detailed statistics provided concerning the R, R-Square, Adjusted
R-Square, and Standard Error of the Estimate. The type of table, the Model Summary, presents
the strength of the relationship between the variables being evaluated. A large R (the multiple
correlation coefficient) suggests a strong relationships. The R Squared depict that, in this
circumstance, 37.7% of the variance is due to the relationship between the dependent and
independent variable.
In Table B3, the ANOVA results are displayed, presenting the Sum of Squares, Degrees
of Freedom, Mean Square, f-statistic and sig. for the Regression, Residual and Total values. The
Regression row displays information about the variation accounted for, while the Residuals rows
displays information about the variation unaccounted for. Because the Regression Sum of
Squares (102911.004) is considerably smaller than the Residual Sum of Squares (619331.574), it
is suggested that most variation between the variables is due to chance and is not of statistical
significance. Furthermore, the significance value (.531) of the f-statistic (.498) is larger than 0.05,
which suggests, once again, that any variance is due to chance. Unfortunately, despite ANOVA’s

ability to portray the degree of variance between variables, it does not suggest the strength of the
relationship. This is why Table B2 displays the Model Summary.
Lastly, in Table B4, the coefficients are shown. These include the B and Std. Error
unstandardized coefficients and the Beta standardized coefficients, as well as the t-statistic and
significance value.
Table B1
Variables Entered/Removeda
Model Variables Entered Variables
Removed
Method
1
Horizontal
hydraulic
fracturingb
. Enter
a. Dependent Variable: Aggravated assault
b. All requested variables entered.
Table B2
Model Summary
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .377a
.142 -.143 454.36093
a. Predictors: (Constant), Horizontalhydraulic fracturing

Table B3
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression 102911.004 1 102911.004 .498 .531b
Residual 619331.574 3 206443.858
Total 722242.578 4
b. Predictors: (Constant), Horizontalhydraulic fracturing
Table B4
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) 1164.877 694.048 1.678 .192
Horizontalhydraulic
fracturing
-292.847 414.773 -.377 -.706 .531

Appendix C
Curve Estimation Model: Curve Fit Regression
In order to further support the statistical significance gathered in the ANOVA regression, Curve
Fits were run for each dependent variable. This graphs display the non-linear relationships
projected between each dependent variable and the independent variable, horizontal hydraulic
fracturing. A linear line is portrayed dependent upon the location of observed factors.
Table C1 provides a summary of the Curve Fit models and parameter estimates. It
includes R-Square, f-statistic, Degrees of Freedom 1, Degrees of Freedom 2 and sig. The
parameter estimates include the constant and the b1. B1 represents that the generated Curve
Estimation Models suggest that past a certain point, increased horizontal hydraulic fracturing
actually decrease the likelihood of negative social conditions. Because the significance value is
greater than 0.05, it is suggested that the variation in between the variables is due to chance.
Displayed upon Tables C2, C3 and C4 are the relationships between the horizontal
hydraulic fracturing and various measurements of social conditions. As each operationalized
measurement of social conditions generated a separate graph, not every graph was included in
this paper; however, an example graph has been included for each type of relationship portrayed.
Table C2 shows a directly proportional relationship. In this circumstance, as the x
variable increase, the y variable increases. When one variable is altered by a certain ratio, the
other variable is altered by the same variable. Therefore, in this case, as Congenital Hypertrophic
Pyloric Stenosis increases, so does the prevalence of horizontal hydraulic fracturing.
Table C3 shows an independent relationship. The x variable has no impact on the y
variable; therefore, the line displayed on the graph is straight and there is no relationship present.

This means that, according to the Curve Fit graph, there is an independent relationship between
Gonorrhea and horizontal hydraulic fracturing.
Table C4 shows also shows a direct relationship. However, unlike with CHPS, as fatal
traffic accidents decrease, the prevalence of horizontal hydraulic fracturing appears to be
decreases.
Table C1
Model Summary and ParameterEstimates
Dependent Variable: Aggravated assault
Equation ModelSummary Parameter Estimates
R Square F df1 df2 Sig. Constant b1
Linear .142 .498 1 3 .531 1164.877 -292.847
The independent variable is Horizontalhydraulic fracturing.

Table C2

Table C3

Table C4

The Social Costs of Horizontal Hydraulic Fracturing - Cumper

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