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

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

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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.

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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

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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.”

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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

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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,

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“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

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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

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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

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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

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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.

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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.

Regression To 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).

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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

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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

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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

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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

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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

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1 .377a .142 -.143 454.36093

a. Predictors: (Constant), Horizontal hydraulic 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), Horizontal hydraulic fracturing

Table B4

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 1164.877 694.048 1.678 .192

26


Horizontal hydraulic

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

27


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 Parameter Estimates

Dependent Variable: Aggravated assault

Equation Model Summary Parameter Estimates

R Square F df1 df2 Sig. Constant b1

Linear .142 .498 1 3 .531 1164.877 -292.847

The independent variable is Horizontal hydraulic fracturing.

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Table C2

29


Table C3

30


Table C4

31

THE SOCIAL COSTS OF HORIZONTAL 32

the social costs of horizontal hydraulic fracturing - cumper

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