# IS THERE AN ASSOCIATION BETWEEN SMOKING AND HYPERTENSION?

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Q1: Is there an association between smoking (Yes/No) and hypertension? (Note: you will need to create a new variable called `SMOKER’ which will contain two groups (`Yes’ or `No’) using information on the number of cigarettes smoked per day). In the new variable name include the number of the dataset you have been assigned e.g if you have been assigned the dataset `Framingham_42.sav’, name the variable `SMOKER_42’.

Analytical plan:

STUDY DESIGN

Observational-Framinton heart study was a cross sectional study

VARIABLES

IV : Smoker –categorical dichotomous

DV : Hypertension – categorical dichotomous

HYPOTHESIS

H0: The proportion of people who smoke is similar for people with hypertension and those without Hypertension

H1: The proportion of people who smoke is different for people with hypertension and those without Hypertension

UNIVARIATE ANALYSIS

Smoker-numerical summary =proportion (or %) of sample with people with smoking habit; graphical summary could be a bar graph {note: since the data is dichotomous it is usually better to summarize numerically}

Hypertension-numerical summary=proportion (or %) of sample with hypertension; graphical summary could be a bar graph.

BIVARIATE ANALYSIS

In this bivariate analysis we do the cross tabulation by contingency which interpret the results between the relation between hypertension and smokers

Numerical summary=2 x 2 contingency table Graphical summary=side –by- side bar chart

STATISTICAL TESTS AND ASSUMPTIONS

Chi-square test of independent .because the table is 2x2 should use Fisher’s exact test or Continuity Correction, rather than Pearson’s Chi-square .I will use Fisher’s exact test.{note:the choice of which test to use is up to you.You should state which test you are going to use and then llist the assumptions for the test}

Fisher’s exact test assumptions :1) observations are independent

SIGNIFICANCE LEVELS

P

Results:

Univariate analysis:

In this sample there are 300 individuals in smoker_29 we have valid individuals of 296 are valid but we have 4 missing. In this sample the 166(55.3%) do not smoke ,130(43.3%) people do smoking as we have 4(1.3%) could not be calculated due to the missing data. Among the same sample 78(26%) are not with incident hypertension,222(74%) are the individuals with hypertension.

The below tables shows the summary on the results provided in the frequency tables.

Statistics

 Smoker_29 Incident Hypertension N valid 296 300 Missing 4 0

SUMMARY TABLE SHOWING UNIVARIABLE ANALYSIS -SMOKER_29

 Frequency Percent Valid Percent Cumulative percent Valid No 166 55.3 56.1 56.1 Yes 130 43.3 43.9 100.0 Total 296 98.7 Missing  999 4 1.3 Total 300 100.0

SUMMARY TABLE SHOWING UNIVARIABLE ANALYSIS - INCIDENT

HYPERTENSION

 Frequency Percent Valid Percent Cumulative Percent Valid   No 78 26.0 26.0 26.0 Yes 222 74.0 74.0 100.0 Total 300 100.0 100.0

Graphical Representation

In univariate analysis the representation is done by bar diagram as they are categorical variable on which incident hypertension on x-axis and count on y- axis .

GRAPH SHOWING UNIVARIATE VARIABLE (INCIDENT HYPERTENSION)

In this bar diagram it shows about the smoker_29 on which count is on y- axis and smoker_29 is on x-axis showing yes and no. The number of people who smoke are more when compared to non smokers .

Bivariate analysis

In this analysis the sample consist of valid individuals of 296(98.7%) and 4(1.3%) are missing

Case processing summary

 Cases Valid Missing Total N Percent N Percent N Percent Incident Hypertension* 296 98.7% 4 1.3% 300 100.0% SMOKER_29

In this contingency table here gives the interpretation of results between the relation of hypertension and smoker_29. Here we have an clear description that there are 31(39.4%) individuals do not smoke have no hypertension,47(60.3%) do smoke but do not have the hypertension. In the same sample individuals 135(61.9%) do not smoke but they have hypertension,83(38.1%)they do smoke and have hypertension.

Incident Hypertension*SMOKER_29 crosstabulation

 SMOKER_29 Total No Yes Incident No Count 31 47 78 Hypertension %within Incident 39.7% 60.3% 100.0% Hypertension Yes Count 135 83 218 %within Incident 61.9% 38.1% 100.0% Hypertension Total Count 166 130 296 %within Incident 56.1% 43.9% 100.0% Hypertension

Incident Hypertension*SMOKER_29 crosstabulation

 SMOKER_29 Total No Yes Incident No Count 31 47 78 Hypertension %within Incident 39.7% 60.3% 100.0% Hypertension Yes Count 135 83 218 %within Incident 61.9% 38.1% 100.0% Hypertension Total Count 166 130 296 %within Incident 56.1% 43.9% 100.0% Hypertension

Graphical representation

In bivariate analysis the relation of incident hypertension and smoker-29 is shown by the side –by-side diagram.

Chi-square analysis:

In this sample we do Chi-square tests because it is the 2x2 contingency table.In this we get the degree of freedom, the continuity correction and Fisher’s exact test are calculated.

For Fisher’s exact test we use two tailed hypothesis. Hence the p-value for this sample is 0.001.this means it is lesser than 0.05.this means we reject the null hypothesis as we do not have any significant analysis and conclude that the proportion of people who smoke is different for people with hypertension and those without Hypertension as we know that the Fisher’s Exact Test observations are independent as it is due to the study design.

The proportion of people who smoke is different for people with hypertension and those without Hypertension the Fisher’s Exact test,p=0.001)

This summary, gives a clear descriptive summary and provides the explanation of the data and the relationship between the smokers_29 and hypertension.

Chi – Square Tests

 Asympotic Exact sig. Exact Sig. Value Df Significance (2-sided) (1-sided) ( 2 sided) Pearson Chi-square 11.477a 1 .001 Continuity correction 10.594 1 .001 Likelihood Ratio 11.440 1 .001 Fisher Exact Test .001 .001 Linear-by-linear 11.438 1 .001 Association 296 N of Valid Cases 11.477a 1 .001

SUMMARY:

This is the data which shows consists of two variables with independent variable as smoker_29 and dependent variable as hypertension these are dichotonomous categorical variables which are done with graphical representation by bar diagrams and bivariate by side by side chart. The statistical analysis is done by chi square test in which fisher exact value i.e p value is 0.001 which is lesser than 0.05 in which we reject the null hypothesis and shows the that the proportion of people who smoke is different for people with hypertension and those without Hypertension

APPENDIX:

Statistics

 Incident SMOKER_29 Hypertension N Valid 296 300 Missing 4 0

FREQUENCY TABLE

SMOKER_29

 Cumulative Frequency Percent Valid Percent Percent Valid No 166 55.3 56.1 56.1 Yes 130 43.3 43.9 100.0 Total 296 98.7 100.0 Missing 999 4 1.3 Total 300 100.0

Incident Hypertension

 Cumulative Frequency Percent Valid Percent Percent Valid  No 78 26.0 26.0 26.0 Yes 222 74.0 74.0 100.0 Total 300 100.0 100.0

CROSS TABS

Case Processing Summary

 Cases Valid Missing Total N Percent N Percent N Percent Incident Hypertension * 296 98.7% 4 1.3% 300 100.0% SMOKER_29

Incident Hypertension * SMOKER_29 Crosstabulation

Count

 SMOKER_29 No Yes Total Incident No 31 47 78 Hypertension Yes 135 83 218 Total 166 130 296

I
ncident Hypertension*SMOKER_29 crosstabulation

 SMOKER_29 No Yes Total Incident No Count 31 47 78 Hypertension % within Incident 39.7% 60.3% 100.0% Hypertension Yes Count 135 83 218 % within Incident 61.9% 38.1% 100.0% Hypertension Total Count 166 130 296

% within Incident

56.1%      43.9%       100.0%

Hypertension

 Chi-Square Tests Asymptotic Significance Exact Sig. (2- Exact Sig. (1- Value df (2-sided) sided) sided) Pearson Chi-Square 11.477a 1 .001 Continuity Correctionb 10.594 1 .001 Likelihood Ratio 11.440 1 .001 Fisher`s Exact Test .001 .001 Linear-by-Linear 11.438 1 .001 Association N of Valid Cases 296

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