Critical Thinking

Introduction infection. Superfund Sites (SFS), which are pieces

 

Introduction

            The immune system is one of the most
important systems in the body since it is responsible for immunity and
protection against foreign diseases and infections. One of the most important
cell types are lymphocytes, which play key roles in identifying foreign
invaders and destroying them, such that they are not longer a threat to the
host. In Non-Hodgkin Lymphoma (NHL), lymphocytes proliferate without control, flood
the circulation, and infiltrate other parts of the body (Shankland, 2012).

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            NHL affects over 20 per 100,000
people every year with around 6 per 100,000 dying from the illness.  In
2017, there were a total of over 72,000 cases with 20,000 corresponding deaths
in the United States (NCI SEER). This shows how NHL is a deadly and nationwide
disease that is a problem for the US. Currently, there is no known single cause
for this specific type of cancer. Rather, it is though that a number of genetic
and environmental factors contribute to its development, such as smoking,
exposure to chemicals/radiation, and infection. Superfund Sites (SFS), which
are pieces of land that have been contaminated and need to be cleaned because
of the potential health risks, may expose adjacent communities to carcinogenic
chemicals that cause NHL (EPA).

            One study determined the effect of
immunoglobulin levels of those living near a SFS. Immunoglobulin are proteins
that are an extremely important part of the immune system since they are
responsible for the removal of viruses and bacteria. In this study, it was
found that there was increased levels of immunoglobulin in those living near
SFS compared to those not living near a SFS. Elevated immunoglobulin levels
means that the body is making more antibodies because something is harming it.

Therefore, it was concluded that there are chemicals or fumes in the SFS are
harming the body and the body has to make more antibodies in response.

Likewise, the chemicals may be harmful to normal cellular processes involving
lymphocytes, and may increase the risk for the development of cancer.

 (Williamson, 2006).

Another
study analyzed if uranium milling and mining activities would increase the
incidence and mortality of lung cancer in underground miners. Milling areas are
considered SFS and they wanted to see the effect of them on the health of
workers. They found that incidence and mortality rates were significantly
higher for men and near the uranium mill. This shows that SFS may contain
chemicals that increase one’s risk for developing cancer. Although NHL was not
explored, the results could be similar (Boice, 2010).

The
main article that had inspired this study was by Dr. Webber and his colleagues.

In this study, he looked at the potential connection between NHL and
residential proximity to SFS in Kentucky. They found that 30% of the patients
lived near a SFS and 94.7% were white and over 70. This shows how chemicals may
trigger NHL and those living near a SFS are at very high risk for NHL (Webber,
2016).

From
these three main studies, a project was developed to see if living in a SFS
county affects incidence and mortality rates of NHL in Connecticut. This
project is a correlation study. The correlation between SFS, age, sex, and
region and the incidence and mortality rates of NHL in CT was examined. This
focused on the rates in CT because no study so far has looked into CT, but
rather larger states such as Kentucky and California. The main purpose of this
project is to determine if SFS are correlated to NHL. So far, there is no main
cause and this study could possibly find one. Age and sex will be accounted for
because most cancer rates are different depending on those variables (Henley,
2016) The two main age groups are 50 and older and 65 and older. These age
ranges were chosen because they were options in the NCI SEER database, which
will be used in this project. In addition,  NHL is more common in older
ages. The most common age for diagnosis of NHL is 67 years old (NCI SEER).

 The NCI SEER database, which stands for the National Cancer Institute of
Surveillance, Epidemiology, and End Results Program, was used because this
database was mentioned in many articles and is one of the largest databases
providing cancer statistics (Henley, 2016). The two sexes are male and female
which were also the only options in the database. The SFS that were analyzed
were the Beacon Heights Landfill in New Haven County, the Barkhamsted New
Hartford Landfill in Hartford County, and the Kellogg-Deering Well Field in Fairfield
County. These are the largest and most dangerous SFS in Connecticut according
to the EPA. The location of these SFS are shown in figure 1.

      Beacon Heights
Landfill, Barkhamsted New Hartford Landfill, and the Kellogg-Deering Well Field
Superfund Sites

 

Figure
1

 

The rates from these
three counties will be compared to the five non-SFS counties which are Tolland,
Windham, New London, Litchfield, and Middlesex. These five counties will act as
the control. The race that will be chosen is “all races.” Race will not be
accounted for because there is not enough data in the system to compare the
individual races.

It was hypothesized
that males over 65 years old living in a SFS would have the highest incidence
and mortality rates. According to previous studies, most patients are over 60
years old and males have the highest incidence rates nationwide (Shankland,
2012), Also, it was proven that those living near SFS in Kentucky have higher
incidence and mortality rates of NHL (Webber, 2016). Therefore, in Connecticut,
it is predicted that the older range for males will have the highest rates
overall.

 

Materials
and Methods

            The database that was used in this study was the NCI SEER
database. The outline of the database is shown in figure 2. The first step that
was done in this project was to access this

Figure 2

database and access
settings so all of the statistics would be for the state Connecticut. Incidence
was tested first. The option “All races” was chosen because this study did not
account for race. The first sex that was tested was males. After the gender was
chosen, each age range was tested. This database would display the data in a
table, Excel sheet, and on a map of CT. After the sex male was tested, female
was tested with each of the age ranges. Then, the option both sexes was chosen
for each age range. After this, the option all ages for each sex range was
tested. Finally, the option both sexes and all ages was tested. These same
exact steps were repeated to collect data for mortality rates.

            The incidence and mortality rates was measured per
100,000 individuals. Incidence rate refers to the total number of new diagnoses
of NHL per year, and mortality rate refers to the total number of deaths due to
the disease per year. Additionally, the confidence intervals was set to the
highest amount which was eight indicating more stability of the data. Once all
of these variables were obtained from the database, a map was generated
dividing Connecticut into their separate counties and filled in with a specific
color where each color indicates a specific interval of the amount of cases per
100,000 and was translated from the key.

When collecting all of
this data, they were placed in table with two columns. The first column would
be the rates for the non-SFS and the second column would be for SFS. After
this, a t-test was performed for each of the groups. Then, the average rate was
calculated for each group as well. All of this testing was performed in Excel.

An example of a table is shown in     Figure 3 where the
yellow boxes represent data points.

Figure 3

Once all of these charts
were created, the averages were placed in a bar graph to have a visual
representation of the data. The data was analyzed by Dr. Dhodapkar.

 

Results

            The average incidence and mortality rates with their
corresponding p-value for each group are shown in figure 5.

Figure 5

Results
show that females over 50 years old had a statistically significant change in
incidence rate from non-SFS to SFS. The average rate in non-SFS was 45.6 (SD =
6.17) and the average rate for SFS was 53.1 (SD = 1.93). The p-value for
this group was 0.05 showing that the results are statistically significant. The
incidence rate had increased by 7.5 from non-SFS to SFS.

            Females of all ages had a
statistically significant change in rate as well. The average rate for non-SFS
was 14.5 (SD = 2) and the average rate for non-SFS was 18.1 (SD= 1). The
p-value was 0.01 which was the smallest p-value of the whole study. This means
that this group had the most statistically significant change in rate from
non-SFS to SFS. Then for both sexes and all age ranges, the p-value was 0.02
indicating that results were statistically significant for this group also. The
highest average SFS incidence rate were in males over 65 years old (mean=127 SD
= 5).

            For mortality, there were no
p-values smaller than or equal to 0.05 so there were no statistically
significant results. The p-values were very high for this section and also for
the incidence rates. The group that had the highest mortality rate were males
over 65 years old (mean=45.7 and SD = 2.3), but it was not significant.

A visual representation of the averages are shown in figures 6 and 7.

Figure 6

Figure 7

Discussion

In
this study, it was explored whether or not counties that contained Superfund
Sites had higher prevelances and/or mortality of NHL, and how the rates varied
across different demographic factors in Connecticut. It was hypothesized that
males over 65 years old living in a SFS would have the highest incidence and
mortality rates. This hypothesis was rejected. The average incidence rate for a
male over 65 was 127 (SD = 5) and average mortality rate was 45.7
   (SD = 2.3) with p=0.11 and p=0.42, respectively.

According to Dr. Shankland and her colleagues, men are more likely to develop
NHL (Shankland, 2012). Dr. Webber also found this in his study when he looked
at incidence rates of NHL in Kentucky. (Webber, 2016) This was found in this
study as well because men had the highest incidence rates overall. Even though
males over 65 had the highest incidence and mortality rates, it was not
statistically significant when being compared to SFS. There is large
probability (11% and 42%) that this happened by chance. Therefore, the
hypothesis was rejected.

The
group which had significant evidence that living in a SFS results in higher
incidence rates of NHL were females over 50 years old. They had the smallest
p-value (p=0.01)  which means that there is a very small probability that
this happened because of chance. This means that NHL is affecting women more
than men in SFS in CT. This was a unique finding because incidence is usually
more common in men, so therefore it was predicted that living in a SFS would
affect men the most, but the opposite was found. An explanation for this may be
because of their occupation. In one article, they looked at different job
occupations and calculated the risk for developing NHL. They proposed that some
jobs may have an increased risk because of that chemical and viral agents the
worker could be exposed to. These chemicals could possibly trigger normal
lymphocytes to abnormally develop. They found that jobs such as driving,
carpentry, metalworking, textile, and constant exposure to pesticides are at a
higher risk of NHL (Aminian, 2012). Therefore, this may be the reason why women
had a significant p-value. Women may happen to have these types of jobs in the
SFS county therefore increasing their incidence rate.

All of
the average incidence rates were higher in the SFS counties compared to the
non-SFS which can be shown in figure 6. For both sexes and all ages, there was
a p-value of 0.02 demonstrating that the increase in rates from non-SFS to SFS
was significant. This means that those who are living in SFS counties are at a
higher risk for developing NHL because of the higher incidence rates in those
counties. These results correspond to the ones Dr. Webber had collected in his
study. He used the NCI SEER database too, but did his study in Kentucky and
found higher incidence rates over all for those living near SFS (Webber, 2016).

 This shows how SFS may be a connected to NHL. Also, a chemical called
trichloroethylene could be found in a SFS. This chemical can cause NHL if one
is exposed to it for a long time. This is often used as an industrial solvent also
showing how having a specific occupation which exposes one to the chemical and
also living near the chemical in a SFS could increase incidence rates of NHL
(Press, 2016).

Mortality
also increased in SFS counties. However, it was not significant for any of the
groups.. The rates were very small overall in Connecticut. The average death
rate 5.36 in SFS and 5.53 for both sexes of all ages. In the United States,
around 6 people are killed per 100,000 showing that the results found in this
study are realistic (NCI SEER).

The
p-values may have been high in the study because of the small sample size.

There were only a total of eight data points so it would be hard to get a
statistically significant p-value. In the future, this same study could be
repeated but instead of comparing counties, groups of towns could be analyzed.

A
limitation in this study was the data available. Race could not be accounted
for because of the lack of data the database obtained. If the database did not
have at least 16 cases for a county, it would not provide an incidence rate per
100,000. Therefore, using a different database would solve this problem and
could be a future study. Another improvement to this study would be to observe
socioeconomic factors. Factors such as county poverty, education, household
income, and living conditions could affect incidence and mortality rates
(Vieira, 2017). The incidence rates may have been higher because many residents
are poor in that specific county. Therefore, this would affect their medical life.

Overall, these factors should be account for in future studies to see if there
is any correlation. Another future study could identify different chemicals in
SFS, and investigate the mechanisms by which they cause NHL. The chemical trichloroethylene has
already been observed, but there are hundreds of other chemicals in SFS (Press, 2016). By analyzing a specific
chemical, the risk could be determined and may come to the finding that SFS are
a cause of NHL.

Overall, this study
examined whether or not SFS would lead to higher incidence and mortality rates.

From the data available, it is concluded that SFS are correlated to NHL, and
may possibly be a cause, for both sexes of all ages and specifically females
over 50 years old. This study may start an initiative to start cleaning SFS if
it is found that SFS do cause NHL and also may be a warning for those living
near SFS.

 

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