IS THERE AN ASSOCIATION BETWEEN SMOKING AND HYPERTENSION?

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

Incident 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