orestebancarabeo-hs312-assignment_unit9_doc

Running head: EPIDEMIOLOGICAL RESEARCH PROJECT 1

Epidemiological Research Project

Oresteban Carabeo

Kaplan University

EPIDEMIOLOGICAL RESEARCH PROJECT 2

Epidemiological Research Project

Research Question

Is Air pollution a primary risk factor contributor for Type 2 Diabetes Mellitus?

The Epidemiological research project proposal will address air pollution (AP) as a

significant risk that contributes to Type 2 Diabetes Mellitus (T2DM) and environmental

exposure applying a research question, protocol, ethics, research, analysis, and dissemination of

results. The purpose of the research study is to assess the effect of environmental air pollution on

the incidence of T2DM, which will take place at the Shanghai clinical center for endocrine and

metabolic diseases (CCEMD) in China. The CCEMD will provide limited funds to cover all the

costs associated with the study that would be one year.

According to Ahearn (2011), the severe air pollution in China is due to rapid

industrialization, urbanization, and motor vehicles growth. For instance, there are “470,000

people in China that have died from exposure to outdoor air pollution in 2000, and each year an

estimated 400,000 premature deaths result from indoor air pollution exposures like coal smoke

from heating and cooking” (Ahearn, 2011, p. 1). Additionally, Rohde and Muller (2015) pose

that the greatest pollution predominates around the East with significant levels across the north

and central China, which widespread intense in a northeast corridor from Shanghai to North

Beijing. The research analysis of the population of China exposes that 92% experienced >120

hours of unhealthy air and 38% experienced average concentrations of harmful exposure. Lastly,

the average exposure of China’s population to “PM2.5 was 52 μg/m3, which the observed air

pollution is intended to contribute to 1.6 million deaths/year in China [0.7–2.2 million

deaths/year at 95% confidence], roughly 17% of all deaths in China” (Rohde & Muller, 2015, p.

1).


According to the World Health Organization (WHO) (2015a), air pollution is an

environmental indoor and outdoor contamination that involves the utilization of chemicals,

physical, and biological agents, which makes a simple modification throughout the atmosphere.

For instance, different types of AP sources are utilized such as domestic burning devices,

automobiles, manufacturing facilities, and forestry fires. Notably, the public health has identified

primary pollutants such as particulate matter, carbon monoxide, ozone, nitrogen dioxide, and

sulfur dioxide (WHO, 2015a). Hence, the air pollution contamination throughout indoor and

outdoor has contributed to fatal cases of respiratory and other diseases, which are a malady to the

world population. In the section about Diabetes, WHO (2015b) explains that T2DM is the results

of the limited body uses of insulin called non-insulin-dependent, which contributes to “90% of

people with diabetes around the world, and is largely the result of additional body weight and

physical inactivity” (para. 5). In addition to that, the year 2014 the global prevalence of diabetes

was around 9% of adults from 18 years and over, which around the year 2012 the death estimate

from the malady was 1.5 million deaths (WHO, 2015b). Moreover, WHO (2015b) projects that

more than “80% of diabetes deaths occur in low-and-middle-income countries, which will

contribute to the 7th principal cause of death by 2030” (“ Key facts”).

Rajagopalan and Brook (2012) posit that the world of technology throughout innovations

and globalization of food services have irrevocably altered energy expenditures within high-

caloric diets and agricultural practices. The focus primarily over the decades has been on

components of urbanization such as inactivity and factors related to nutrition. In addition to that,

some observations linked the exposure to environmental factors such as air and water that are a

propensity to chronic diseases. These results provide evidence on the outdoor air pollution

relation with urbanization and the emergence of cardiometabolic diseases, which emphasizes on


T2DM. The environment of T2DM alters in susceptibility the pathophysiology of coronary and

cerebrovascular, and peripheral arterial disease, which relates cardiometabolic with the

confluence of cardiovascular diseases. Furthermore, the environmental exposures are associated

with metabolic diseases that demonstrate the persistent organic pollutants such as toxins that link

within insulin resistance (IR) and T2DM. Lastly, there is evidence with a prospective cohort

research within individuals who were exposed to “2,3,7,8-tetrachlorodibenzop-dioxin or other

persistent organic pollutants in occupational and other settings that have reported increased risk

of T2DM and IR” (Rajagopalan & Brook, 2012, p. 3037).

Rajagopalan and Brook (2012) pose a study in the Boston residential area where six-day

moving averages of particulate matter PM2.5 with black carbon (BC) were related to diminishing

vascular reactivity between diabetic patients, in which the effects were stronger in T2DM than

Type 1 Diabetes. Notably, the blood samples provided from other clinical trials within the

Boston area reveals BC concentrations from a regionally monitoring station, which were

significantly related to increment levels of inflammatory indicators. Furthermore, these findings

are supported by a prospective study panel from a small population of T2DM patients, which

flow-mediated dilatation within the first 24 hours decreased with PM2.5.

The PM2.5 associations diminutions related to the endothelial function were larger

between individuals with hemoglobin A1C (HbA1c), low adiponectin, and elevations during the

examination day of myeloperoxidase levels. Indeed, these results were associated with

alterations in vascular tone along with inflammation that could pose potential mechanisms of

susceptibility (Rajagopalan & Brook, 2012). Rajagopalan and Brook (2012) suggest that there

are primary tools of evidence with Diabetes associated with air pollution, which PM2.5

contributes as a mediator of endothelial dysfunction with IR. These findings reveal that air


pollution exposure modifies the endothelial function in animals and humans, which precede to

changes in the IR implicating a peripheral reduction within the glucose uptake. Notably, the

results of the first experimental investigation expose the connecting association with inhalational

PM2.5 exposure with T2DM, high-fat diet feeding, fasting increments, postprandial glucose,

insulin, and Homeostasis Model Assessment-IR (HOMA-IR) actions. The PM exposure creates

an elevation in prothrombotic adipokines, increased adhesion circulation molecules such as

plasminogen activator inhibitor 1, intracellular adhesion molecule-1, and E-selectin. Moreover,

the exposure of PM associates within impairment in phosphatidylinositol 3-kinase-Akt-

endothelial nitric oxide synthase, which signals in the aorta, and diminish tyrosine

phosphorylation of IRS-1 in the liver. These results provide the evidence of the signal

abnormality of insulin throughout the vasculature. Another important concept to introduce is the

integrated model of mechanism, which involves in air pollution that mediated Diabetes to how

many signals perceived in the lungs leads to metabolic pathology (Rajagopalan & Brook, 2012).

Rajagopalan and Brook (2012) reveal that chronic inflammation and metaflamation

occurs because of the exposure to air pollution, which represents within T2DM and obesity a

potential risk of pollution exposure, and metabolic dysfunction. It should be noted, T2DM in

humans and animals models are associated with increments levels of inflammatory cytokines,

recruitment, and activation of innate immune cells depots like the visceral adipose. The over

activity of the sympathetic nervous system (SNS) exacerbates insulin resistance, which alters the

autonomic balance throughout inflammatory pathways such as air pollutant (Rajagopalan &

Brook, 2012).


Protocols

The study design for the population of China will combine observational, analytical,

case-control pre-eliminating study, and a prospective cohort long-term project. The investigation

will include the population size of China of 1 million healthy adult individuals between the ages

of 18<45 years that have not contracted the T2DM disease. The sample size from the population

of China for the study will be 9513 human subjects combined with 95% confidence intervals, 1%

margin of error, and random sampling selection. Matthews and Kostelis (2011) reveal that the

best way to access the sample is through electronic emails, a Wed-based survey with options,

and questionaries’ administration. Bonita, Beaglehole, and Kjellström (2006) reveal that

observational, analytical studies provides the researcher with measures and does not intervene

allowing the environment to take its course that analyzes the association between health status

and other variables such as air pollution. The study could start with a pre-eliminated case control

to investigate causation. Bonita, et al. (2006) posit that case-control studies examine causes of

disease in a simple way to compare or reference a suitable control group unaffected by the

illness, which examines the occurrence of possible causes within cases, and in controls. The

researchers will collect data for the study at a point of time for occurrence disease and

throughout a previous time the exposures, which Case-control studies are retrospective because

investigators look back from the disease to a probable cause (Bonita, et al., 2006).

The cohort studies will help determine the association between males and females in

regards to the incidence level of exposure to AP and T2DM. Bonita, et al. (2006) pose that

cohorts are follow-up and incidence studies that expose a group who are free of disease

classifying them into subgroups, which accords to the exposure of a potential cause of illness.

The variables of interest are specified and measured through the whole cohort study follow up to


see the following developments of new cases of T2DM disease, which differs between exposure

groups, and without exposure. Moreover, prospective cohort studies relate to the collected data

time and does not relate to the exposure, and effect. The best information in regards to disease

causation and risk measurement developing disease contributes to cohort studies, which

undertake longer periods of follow up because the disease may occur longer time after exposure.

On the other hand, the ideal method for potential confounding variables to be distributed equally

between comparing groups is randomization. The sample size of the population of China is large

enough that avoids maldistribution of the sample random variables (Bonita, et al., 2006).

Ethical Approval

When considering the commencement research proposal is important to abide all rules

and regulations of ethics that concern with human subjects. Matthews and Kostelis (2011)

explains that ethics involves the principles obligations of knowing what is right and wrong in a

behavior manner. The research proposal should consider various associations for “ethical issues

such as the American Psychological Association (APA), Department of Health and Human

Services (HHS), National Institutes of Health (NIH), and World Medical Association (WMA)”

(Matthews & Kostelis, 2011, p. 146). For example, the German investigators during World War

II utilized concentration camps to do research with human subjects without their consent. The

nefarious intentions of the research conducted on human subjects have led to taking German

physicians to trial for their medical experiments that appear in the Nuremberg War Crimes.

These trial results concluded with the development of the Nuremberg Code of 1947 that provides

ten principles, which govern the conduct of ethics within human subjects (Matthews & Kostelis,

2011).


Bonita, et al. (2006) posit that all epidemiological research involving human subjects

must be review by the ethical review committee for approval. These principles of research apply

to the epidemiological practice of ethics, which requires informed consent, confidentiality,

respect for human rights, and scientific integrity. For instance, the informed consent human

subjects who participate must be voluntary informed before entering into a research study

retaining the right to withdraw at their convenience. Then, researchers have the obligation to

protect the confidentiality information acquired from participants and research studies. Further,

the respect for individual rights can create some tension because of the group and individual

interests. A good illustration that will provide the respect for individuals rights would be Cuba,

which contained the HIV/AIDS spread applying testing to individuals at risk, and segregating the

infected people from the whole population. Lastly, scientific integrity reveals that scientists have

the potential to act unethically within research because of pressure to succeed. Scientists are

influenced by a conflict of interest and fabricated data publication results (Bonita, et al., 2006).

Research and Analysis

The SPSS version 2.0 will produce the data for the sample size of the population of China

utilizing linear regression, descriptive statistics, inferential statistics, Pearson correlation,

ANOVA, coefficients, and scatterplot analysis. The descriptive statistics will provide a

computation of data to describe or illustrate the collected sample for the research study. These

statistical measures will demonstrate if there is an association between air pollution and T2DM

incidence within genders. Then, the inferential statistics will help compute the data statistics to

answer the research question regarding the air pollution as a primary risk factor contributor for

Type 2 Diabetes Mellitus. Bonita, et al. (2006) expose that using a sample to make inferences

about the population of China is the most significant part of research within epidemiology, which


takes the sample size, and make a generalization about a population. These likely results could

be illustrated with the sample mean, variance, and other numbers, which summarizes the

population as parameters. The confidence interval will utilize rational limits for the population

mean regarding from the information of the sample, which 95% will expose the true value of the

population mean of China, and the other 1% would not. On the other hand, the utilization of

regression models are the best tools for data analysis throughout research studies that will

provide an association between AP and T2DM using linear regression. For instance, the standard

Analysis of Variance (ANOVA) can provide a simple linear regression and multiple linear

regression such as dependent variables like body and weight, which are a continuous measure,

and independent can be both with continuous and categorical (Bonita, et al., 2006).

The analysis research proposal will provide qualitative with quantitative variables for the

scatterplot that combines independent explanatory variables such as genders and dependent

response variables, which will address AP, and T2DM incidence. Matthews and Kostelis (2011)

exhibit the importance to test the null and alternative hypothesis, which includes no significance

between the expected statistics, and the opposite of the null hypothesis. For example, the alpha

levels to determine statistical significance to review the hypothesis are necessary such as

significance level (p), which utilizing an alpha level p < .05 is significant, and p >.05 will not be

statistically significant (Matthews & Kostelis, 2011).

Dissemination of Results

This epidemiological research proposal suggests ways to help the public health and

governmental sectors in creating new policies to measured health prevention for AP and T2DM.

Hence, the research discoveries will provide detailed findings to all participants. Also, the

dissemination of results will produce a report for the Shanghai Clinical Center for Endocrine and


Metabolic Diseases (CCEMD) in China, the World Health Organization, and the American

Diabetes Association. Indeed, these dissemination reports will enhance the delivery of care

within the world population throughout international and national journals. In addition, the

presentation of papers at nationwide and international conferences will benefit the world media

by providing different results between AP and T2DM, which enhances the comparison baseline

for researchers. Finally, the research outcomes will provide solutions for the manufacturers that

will help alleviate the AP by creating a mechanism to produce new products that will not affect

the health of individuals in contracting the T2DM disease.


References

Ahearn, A. (2011). Air Pollution in China, with Junfeng (Jim) Zhang...Junfeng (Jim)

Zhang. Environmental Health Perspectives, 119(6), 1-5. doi:10.1289/ehp.trp060811

Bonita, R., Beaglehole, R., & Kjellström, T. (2006). Basic epidemiology 2nd edition. Geneva,

Switzerland: WHO Press

Matthews, T. D., & Kostelis, K. T. (2011). Designing and conducting research in health and

human performance. San Francisco, CA: John Wiley & Sons

Rajagopalan, S., & Brook, R. D. (2012). Air pollution and type 2 diabetes: mechanistic

insights. Diabetes, 61(12), 3037-3045. doi:10.2337/db12-0190

Rohde, R. A., & Muller, R. A. (2015). Air Pollution in China: Mapping of Concentrations and

Sources. Plos ONE, 10(8), 1-14. doi:10.1371/journal.pone.0135749

World Health Organization. (2015a). Air pollution. Retrieved from

http://www.who.int/topics/air_pollution/en/

World Health Organization. (2015b). Diabetes. Retrieved from

http://www.who.int/mediacentre/factsheets/fs312/en/

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