• Description of the steps you took to conduct your statistical analyses.
  • Summary of your statistical ***
    • Narrative description
    • Tables and graphs (Be careful – too many tables and graphs decreases clarity)
    • Be sure to include your SPSS codebook as well as the syntax code used in SPSS to conduct your statistical analyses. The page length of your code may vary according to the types of analyses conducted.

    **Please include the following header on this Assignment.**One simple statement for each. This helps you and the instructor keep track of what you are attempting.
    RQ:
    Dependent Variable:
    Independent Variable(s):
    Null Hypothesis:
    Alternate Hypothesis:
    Statistical Test: 

     use the dataset and template document attached. Please follow the research question you proposed and follow the sections found in the template including the graphs. Please state the steps you followed with SPSS to produce all descriptive statistics, graphs and crosstabs. Please provide the crosstab tables of your independent variables and your outcome, one at a time. You can also run modeling. Please note that if you have installed the newest SPSS version, the analyze tab is the first tab, the one adjacent to the print tab. 

PUBH-6033/8033: Final Project Results Template

Results (1 page of narrative plus charts and SPSS syntax code)

In Week 9, you are asked to prepare the Results to your Final Project. It should include the following components:

· Description of the steps you took to conduct your statistical analyses.

· Summary of your statistical findings**

. Narrative description

. Tables and graphs (Be careful–too many tables and graphs decreases clarity)

· Be sure to include your SPSS codebook as well as the syntax code used in SPSS to conduct your statistical analyses. The page length of your code may vary according to the types of analyses conducted.

**Note: Do not attempt to explain your results in this section; only report your findings

Following is a template for how the Results might look for a research question that includes two categorical variables and involves Chi-square analysis. Note that when you report statistical findings in APA style, you do not cut-and-paste tables from SPSS. They must be reformatted and summarized into Word tables. Your Results should include the same components in this order but the specifics should be relevant to your dataset, research question, and variables. Be sure to refer to feedback from your Week 7 assignment to make sure you have selected the right statistical test for your study. ____________________________________________________________________________________

**Please include the following header on this Assignment.**

One simple statement for each. This helps you and the instructor keep track of what you are attempting.

RQ: Dependent Variable: Independent Variable(s):

Null Hypothesis: Alternate Hypothesis: Statistical Test:

RQ: Is there an association between [independent variable] and [dependent variable]? Dependent Variable: [Choose one: Malaria, AIDS(CD4), CHD, Diabetes (Plasma Glucose Concentration), Pancreatic Cancer] Independent Variable(s): [Choose one or two: Gender, Age, Race, Ethnicity, Education, Insurance, Region, BMI, Cholesterol, Alcohol, Tobacco, IDU, Condom, Exercise, Fruit/Vegetable]

Null Hypothesis: There is no association between [independent variable] and [dependent variable]. Alternate Hypothesis: There is an association between [independent variable] and [dependent variable].

Statistical Test: [Depends on variables in RQ]

___________________________________________________________________________________

Results

Statistical analysis steps

Statistical analysis was conducted in SPSS version 21. First the asbestos.sav dataset was uploaded to SPSS and checked for errors. Second, descriptive statistics were run on variables relevant to this study using the following steps: >Analyze > Descriptive Statistics > Frequencies. Pie charts were indicated under the Charts box to visualize the data. Finally, Chi-square analysis was performed using the following steps: >Analyze > Descriptive Statistics >Crosstabs. The independent variable “asbestos” was moved to the Row box and the dependent variable “lungca” was moved to the Column box. Chi-square was clicked under the Statistics button and then OK.

Findings

The asbestos.sav dataset included 285 valid cases. One-third of cases (33.3%) had lung cancer (Figure 1) and 41.4% had been exposed to asbestos (Figure 2). Of the 118 cases that had been exposed to asbestos, 80 had lung cancer and 38 did not have lung cancer. Chi-square analysis showed that there was a statistically significant association between asbestos exposure and lung cancer, Χ2 (1, N=285) = 107.631, p<.01 (Table 1).

Figure 1

Frequency of Lung Cancer Cases in Sample

Figure 2

Frequency of Asbestos Exposure in Sample

Table 1

Results of Chi-square Test and Descriptive Statistics for Lung Cancer by Asbestos

Lung Cancer

Asbestos

Yes

No

Yes

80 (84%)

38 (88%)

No

15 (16%)

152 (12%)

Note. 2 = 107.631, df = 1. Numbers in parentheses indicate column percentages.

* p < .01

Codebook and Syntax

CODEBOOK asbestos [n] lungca [n]

/VARINFO POSITION LABEL TYPE FORMAT MEASURE ROLE VALUELABELS MISSING ATTRIBUTES

/OPTIONS VARORDER=VARLIST SORT=ASCENDING MAXCATS=200

/STATISTICS COUNT PERCENT MEAN STDDEV QUARTILES.

Codebook

Notes

Output Created

27-APR-2015 13:36:13

Comments

Input

Data

C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

285

Syntax

CODEBOOK asbestos [n] lungca [n]

/VARINFO POSITION LABEL TYPE FORMAT MEASURE ROLE VALUELABELS MISSING ATTRIBUTES

/OPTIONS VARORDER=VARLIST SORT=ASCENDING MAXCATS=200

/STATISTICS COUNT PERCENT MEAN STDDEV QUARTILES.

Resources

Processor Time

00:00:00.02

Elapsed Time

00:00:00.03

[DataSet2] C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

asbestos

Value

Count

Percent

Standard Attributes

Position

2

Label

<none>

Type

String

Format

A3

Measurement

Nominal

Role

Input

Valid Values

1

Yes

118

41.4%

2

No

167

58.6%

lungca

Value

Count

Percent

Standard Attributes

Position

3

Label

<none>

Type

String

Format

A3

Measurement

Nominal

Role

Input

Valid Values

1

Yes

95

33.3%

2

No

190

66.7%

FREQUENCIES VARIABLES=asbestos lungca

/STATISTICS=MINIMUM MAXIMUM

/PIECHART FREQ

/ORDER=ANALYSIS.

Frequencies

Notes

Output Created

27-APR-2015 12:57:53

Comments

Input

Data

C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

285

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics are based on all cases with valid data.

Syntax

FREQUENCIES VARIABLES=asbestos lungca

/STATISTICS=MINIMUM MAXIMUM

/PIECHART FREQ

/ORDER=ANALYSIS.

Resources

Processor Time

00:00:00.20

Elapsed Time

00:00:00.19

[DataSet2] C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

Statistics

asbestos

lungca

N

Valid

285

285

Missing

0

0

Frequency Table

asbestos

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

118

41.4

41.4

41.4

No

167

58.6

58.6

100.0

Total

285

100.0

100.0

lungca

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Yes

95

33.3

33.3

33.3

No

190

66.7

66.7

100.0

Total

285

100.0

100.0

Pie Chart

CROSSTABS

/TABLES=asbestos BY lungca

/FORMAT=AVALUE TABLES

/STATISTICS=CHISQ

/CELLS=COUNT

/COUNT ROUND CELL.

Crosstabs

Notes

Output Created

27-APR-2015 12:58:42

Comments

Input

Data

C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

Active Dataset

DataSet2

Filter

<none>

Weight

<none>

Split File

<none>

N of Rows in Working Data File

285

Missing Value Handling

Definition of Missing

User-defined missing values are treated as missing.

Cases Used

Statistics for each table are based on all the cases with valid data in the specified range(s) for all variables in each table.

Syntax

CROSSTABS

/TABLES=asbestos BY lungca

/FORMAT=AVALUE TABLES

/STATISTICS=CHISQ

/CELLS=COUNT

/COUNT ROUND CELL

/BARCHART.

Resources

Processor Time

00:00:00.12

Elapsed Time

00:00:00.13

Dimensions Requested

2

Cells Available

131029

[DataSet2] C:UsersaferraroDocumentsWaldenClasses6125Datasetsasbestos.sav

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

asbestos * lungca

285

100.0%

0

0.0%

285

100.0%

asbestos * lungca Crosstabulation

Count

lungca

Total

Yes

No

asbestos

Yes

80

38

118

No

15

152

167

Total

95

190

285

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Pearson Chi-Square

107.631a

1

.000

Continuity Correctionb

105.000

1

.000

Likelihood Ratio

113.604

1

.000

Fisher's Exact Test

.000

.000

N of Valid Cases

285

a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 39.33.

b. Computed only for a 2×2 table

image1.png

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2

Project Methods

Name

Institution

Course

Professor

Date

Project Methods

RQ: What is the relationship between tobacco consumption, as measured by packs smoked per day, and the risk of pancreatic cancer?

Dependent variable: Pancreatic cancer

Independent variable(s): Tobacco consumption (packs smoked per day)

Null Hypothesis: There is no association between tobacco consumption and the risk of pancreatic cancer.

Alternate Hypothesis: There is an association between tobacco consumption and the risk of pancreatic cancer.

Statistical Tests: Logistic Regression and Independent T-test

Public health significance:

Pancreatic cancer is a primary public health concern, with an estimated 11% 5-year survival rate as of 2024. This approximation translates to about 64,050 new reported cases in the United States by 2024. Tobacco use is a major modifiable risk factor; smokers have a 2- to 3-times increased risk of developing pancreatic cancer compared with non-smokers. Understanding this relationship is essential for appropriately tailoring prevention strategies.

Methods

Study sample

The study's sample included 280 participants from ages 18 to 64, including individuals with and without pancreatic cancer. This diverse sample allows comparisons between cases and controls across various age groups.

Data collection

Data were collected through medical record reviews, cancer registry queries, and self-administered questionnaires. Medical records and cancer registries were used to obtain diagnostic confirmation and clinical characteristics of pancreatic cancer cases. Questionnaires collected self-reported information on demographics, behavioral risk factors such as tobacco use (measured as packs smoked per day), and validation of cancer threats.

Primary variables

The dependent variable was pancreatic cancer (yes or no). The independent variable was tobacco consumption (packs smoked per day). Demographic factors and other potential risk factors, including age, sex, race, BMI, alcohol use, and exercise habits, are additional control variables to control for confounding.

Statistical analyses

Statistical analyses will begin with descriptive statistics to characterize the study population. For continuous variables (age, tobacco consumption), means and standard deviations will be calculated. For categorical variables (gender, pancreatic cancer), frequencies and percentages will be reported. Two primary analyses will be conducted. All statistical metrics will be synthesized using SPSS software under p < .05 significance level. An independent t-test will compare the mean tobacco consumption between pancreatic cancer cases and controls to determine if a significant difference exists between these groups.

Conversely, logistic regression will analyze the connection between the risks of pancreatic cancer posed by tobacco utilization while controlling for potential confounding variables like age, gender, and other risk factors. Pancreatic cancer is the dependent variable, while tobacco consumption is the primary independent variable and covariate, providing adjusted odds ratios and quantifying the association between tobacco consumption and pancreatic cancer risk. The analysis will explore a dose-response relationship by categorizing tobacco consumption into levels (e.g., non-smokers, light, moderate, and heavy smokers) and examining the trend in pancreatic cancer risk across these categories.

References

American Cancer Society. (2024). Cancer Facts & Figures 2024. Www.cancer.org. https://www.cancer.org/research/cancer-facts-statistics/all-cancer-facts-figures/2024-cancer-facts-figures.html

Hu, J.-X., Zhao, C.-F., Chen, W.-B., Liu, Q.-C., Li, Q.-W., Lin, Y.-Y., & Gao, F. (2021). Pancreatic cancer: A review of epidemiology, trend, and risk factors. World Journal of Gastroenterology, 27(27), 4298–4321. https://doi.org/10.3748/wjg.v27.i27.4298

Molina-Montes, E., Van Hoogstraten, L., Gomez-Rubio, P., Löhr, M., Sharp, L., Molero, X., Márquez, M., Michalski, C. W., Farré, A., Perea, J., O’Rorke, M., Greenhalf, W., Ilzarbe, L., Tardon, A., Gress, T. M., Barberà, V. M., Crnogorac-Jurcevic, T., Muñoz-Bellvis, L., Domínguez-Muñoz, E., & Balsells, J. (2020). Pancreatic Cancer Risk in Relation to Lifetime Smoking Patterns, Tobacco Type, and Dose–Response Relationships. Cancer Epidemiology, Biomarkers & Prevention, 29(5), 1009–1018. https://doi.org/10.1158/1055-9965.EPI-19-1027

Weissman, S., Takakura, K., Eibl, G., Pandol, S. J., & Saruta, M. (2020). The Diverse Involvement of Cigarette Smoking in Pancreatic Cancer Development and Prognosis. Pancreas, 49(5), 612–620. https://doi.org/10.1097/MPA.0000000000001550

,

2

Interpretation and Application of Data

June 23rd, 2024

Interpretation and Application of Data

Introduction

The pancreas is a critical organ that plays a significant role in metabolic and digestive functions. However, the prognosis for pancreatic cancer stays poor, rendering it the third leading factor in cancer mortality, with an exponentially growing rate regardless of demographic characteristics.

This study examines the association between tobacco use and pancreatic cancer diagnosis. Tobacco consumption impacts risk, and clarifying its role informs prevention. The study studies tobacco in packs per day and the risk of pancreatic cancer diagnosis. Recent systematic literature has guaranteed a connection between smoking and pancreatic cancer. However, additional reviews are critical while concluding relationships when different variables are controlled.

Research question: What is the relationship between tobacco consumption, as measured by packs smoked per day, and the risk of pancreatic cancer diagnosis? Dependent variable: Pancreatic cancer. Independent variable: tobacco consumption (packs smoked per day) Null hypothesis: There exists no relationship between tobacco consumption and the risk of pancreatic cancer. Alternate hypothesis: There exists a relationship between tobacco consumption and the risk of pancreatic cancer.

Annotated Bibliography

Bibliography 1:

Edirisinghe, S., Weerasekera, M., De Silva, D., Liyanage, I., Niluka, M., Madushika, K., Deegodagamage, S., Wijesundara, C., Rich, A., De Silva, H., Hussaini, H., De Silva, K., & Yasawardene, S. (2022). The Risk of Oral Cancer among Different Categorise Tobacco Smoking Exposure in Sri Lanka. Asian Pacific Journal of Cancer Prevention, 23(9), 2929–2935. https://doi.org/10.31557/apjcp.2022.23.9.2929

This source examines the risk of oral cancer based on different categories of tobacco smoking exposure in Sri Lanka. A case-control study incorporated 105 patients with oral cancer and 210 controls. The investigation discovered that the number of cigarettes smoked each day and the consolidated utilization of betel quid and smoking are critical threats to cancer among Sri Lankans. While this source fails to examine the connection between tobacco and pancreatic cancer explicitly, it gives significant information on the disease risk from various degrees of tobacco consumption.

Bibliography 2:

Mohammad Moein Vakilzadeh, Reza Khayami, Danyal Daneshdoust, Reza Moshfeghinia, Farzad Sharifnezhad, Zahra Taghiabadi, Hanieh Keikhay Moghadam, Mohammad Ali Karimi, Ghorbani, A., Pegah Bahrami Taqanaki, Nima Boojar, Azarshab, A., Soodabeh Shahidsales, & Reihaneh Alsadat Mahmoudian. (2024). Prevalence of tobacco use among cancer patients in Iran: a systematic review and meta-analysis. BMC Public Health, 24(1). https://doi.org/10.1186/s12889-024-18594-8

This source provides details regarding a deliberate survey and meta-analysis of the pervasiveness of tobacco consumption among cancer patients in Iran. It surveyed 26 studies involving more than 32,000 cancer patients. The investigation revealed that the patients shared 33.7% of current tobacco use and 12.9% of previous tobacco use. Although the source fails to examine tobacco usage in relation to cancer rates directly, it provides an important foundation for tobacco use trends among Iranian cancer patients.

Bibliography 3:

Scherübl, H. (2022). Tobacco Smoking and Gastrointestinal Cancer Risk. Visceral Medicine, 1–5. https://doi.org/10.1159/000523668

This study examined the relationship between tobacco use and several gastrointestinal cancers, showing that anal, esophageal, gastric, pancreatic, biliary, hepatocellular, and colorectal cancers are all brought on by tobacco use. On pancreatic cancer specifically, this manuscript reveals that cigarette smoking approximately doubles the relative risk, and smoking intensity is an increasing risk. It also reports that smoking cessation can help reduce excess pancreatic cancer risk. This source directly examines the link between tobacco consumption and pancreatic cancer risk.

Bibliography 4:

Weber, M. F., Sarich, P. E. A., Vaneckova, P., Wade, S., Egger, S., Ngo, P., Joshy, G., Goldsbury, D. E., Yap, S., Feletto, E., Vassallo, A., Laaksonen, M. A., Grogan, P., O’Connell, D. L., Banks, E., & Canfell, K. (2021). Cancer incidence and cancer death in relation to tobacco smoking in a population‐based Australian cohort study. International Journal of Cancer, 149(5), 1076–1088. https://doi.org/10.1002/ijc.33685

This cohort study examined information from over 229,000 Australian respondents to investigate the connection between smoking history, cancer frequency, and mortality. The outcomes show that current smokers have an expanded risk of pancreatic cancer compared with non-smokers. Risk also increases, corresponding to smoking intensity. This source provides additional evidence on the positive association between tobacco consumption and pancreatic cancer risk, based on a large population-level cohort from Australia.

Statistical Test Data Dictionary:

References

Edirisinghe, S., Weerasekera, M., De Silva, D., Liyanage, I., Niluka, M., Madushika, K., Deegodagamage, S., Wijesundara, C., Rich, A., De Silva, H., Hussaini, H., De Silva, K., & Yasawardene, S. (2022). The Risk of Oral Cancer among Different Categorise Tobacco Smoking Exposure in Sri Lanka. Asian Pacific Journal of Cancer Prevention, 23(9), 2929–2935. https://doi.org/10.31557/apjcp.2022.23.9.2929

Mohammad Moein Vakilzadeh, Reza Khayami, Danyal Daneshdoust, Reza Moshfeghinia, Farzad Sharifnezhad, Zahra Taghiabadi, Hanieh Keikhay Moghadam, Mohammad Ali Karimi, Ghorbani, A., Pegah Bahrami Taqanaki, Nima Boojar, Azarshab, A., Soodabeh Shahidsales, & Reihaneh Alsadat Mahmoudian. (2024). Prevalence of tobacco use among cancer patients in Iran: a systematic review and meta-analysis. BMC Public Health, 24(1). https://doi.org/10.1186/s12889-024-18594-8

Scherübl, H. (2022). Tobacco Smoking and Gastrointestinal Cancer Risk. Visceral Medicine, 1–5. https://doi.org/10.1159/000523668

Weber, M. F., Sarich, P. E. A., Vaneckova, P., Wade, S., Egger, S., Ngo, P., Joshy, G., Goldsbury, D. E., Yap, S., Feletto, E., Vassallo, A., Laaksonen, M. A., Grogan, P., O’Connell, D. L., Banks, E., & Canfell, K. (2021). Cancer incidence and cancer death in relation to tobacco smoking in a population‐based Australian cohort study. International Journal of Cancer, 149(5), 1076–1088. https://doi.org/10.1002/ijc.33685

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