Lifestyle Impact on Cardiovascular Health: Data Analysis Assignment Sample

Lifestyle Impact on Cardiovascular Health: Data Analysis

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Chapter 1: Introduction-Data Analysis And Interpretation: Impact Of Lifestyle On Cardio-Vascular Health

1.1 Introduction

Development of cardiovascular problems among the old and also in the young population is very common nowadays. Several reasons are underlying for this serious and detrimental health condition. Among all other causative measurements, the first and foremost affecting factor is the shape of dealing with everyday lifestyle. Uncontrolled and unhealthy ways of life designs including food utilisation and deficient actual exercise have prompted cardiovascular illness at an early age. This has been found in past examinations that there are a few connections between these variables with heart infection events. For accomplishing the plan to observe connection among way of life and cardiovascular issues this examination has been performed.

1.2 Research background

In the UK it has been observed that most of the populace has been enduring a few issues like diabetes, elevated cholesterol, and heftiness and so on and these extensively affect the cardiovascular sickness advancement. Because of this issue, the way of life of the populace should be amended and a solid way of lifestyle can diminish the impact of cardiovascular sickness improvement. In the UK a few examinations have been directed on this issue (Foster et al. 2018). 

1.3 Research aim and objective

The aim of this research is to analyse the effect of lifestyle among UK people for developing cardiovascular disease. Also, to offer a healthy lifestyle perspective among people for minimising the risk of cardiovascular disease by detecting potential risks associated with cardiovascular disease among patients. 

In order to achieve the aim, this research has followed some objectives linked with the aim. These objectives are:

• To observe the link between lifestyle and cardiovascular disease for obtaining the impact on the population.
• To analyse the alcohol consumption and smoking pattern among people for understanding the effect on cardiovascular disease development.
• To evaluate the Fibrinogen level and BMI rate among people for analysing its impact on cardiovascular disease development.

1.4 Research question

As per the research and its targeted finings, the main question associated with this research is:

1. Is there any effect of lifestyle among people who are suffering from cardiac disease and also the underlying correlation between cardiovascular disease and lifestyle management in the UK population?

1.5 Research hypothesis

Hypotheses related with this research are provided with some assumptions related with this research-based study. These are:

H1: There is a link between health and lifestyle to influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

H0: There is no link between health and lifestyle influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

H2: The alcohol consumption and smoking pattern among people can influence the development of cardiovascular disease in an individual.

H0: The alcohol consumption and smoking pattern among people cannot influence the development of cardiovascular disease in an individual.

 H3: The Fibrinogen level and BMI rate among people have an impact on cardiovascular disease development.

H0: The Fibrinogen level and BMI rate among people don't have any impact on cardiovascular disease development.

Chapter 2: Methodology

A) Study design and data collection

The design of this study is following the correlational study design. This design has forecasted the variables and also measured the impact of these variables on the development of cardiovascular disease. This implies that the effect of alcohol consumption and smoking habit on cardiac conditions, i.e., whether high alcohol consumption rate increases the chances of cardiac problems or not and also whether lowering down the smoking pattern can reduce the chances of cardiovascular disease development; this has been analyzed with this particular study design. Descriptive analysis related to this research has helped in identification and interpretation of the analytical outcome.

The process of Data collection

After collecting the data about lifestyle, health effects, and socio - demographic variables from a sample of adults in the UK. With the obtained primary information, a comprehensive SPSS analysis was performed, and numerous outcomes, comprising statistical analysis on certain descriptive changes, were created (Gong et al. 2019). 

B) Data analysis

The analysis of data has been followed by a primary data analysis method with a data secondary source-based data collection. The variables which are associated with the data collection of secondary analysis included smoking habit, alcohol consumption, blood pressure rate, BMI rate and fibrinogen level among selected sample sizes. These variables have been analysed with the help of SPSS software which is mainly used for the purpose of statistical data interpretation and also for understanding different demographic correlational effects in terms of development of relatable conditions (Said et al. 2018). This method has been performed and followed with the help of a rigorous and structured statistical analysis performance which have included theregression model, ANOVA test, chi square test, t test and descriptive statistics for each variable. Other descriptive statistics such as frequency model of the respondent have been included in each of the statistical outcomes. From these statistical views, it is found that hypotheses will be tested properly. This assignment mainly focuses on the hypotheses regarding the link among the health and lifestyle to influence the blood pressure level and cardiovascular disease for obtaining the impact on the population. Not only this, through these statistical views, it clearly results among the rate of the consumption and the pattern of the smoking. Through this different statistical analysis, the impact of the BMI rate is also identified. At the time of the data analysation, some coding is discussed. At the time of the marital status, -1.000 is represented those persons who are not applicable in this study. They may be in the child category or non-smoker. 1.00 stands for the married persons, they may be male or female. 2.00 represents the cohabiting categories. 3.000 is representing the Single persons. 4.000 is representing the widow categories. 5.000 is represented by the divorced persons. 6.000 is representing the separated one. The last category was that type of person who is not responding in this case. It is represented by the 9.000. That type of coding is also generated for the response of the persons. The first category, who are not responding to this survey, are denoted by the -1.000. The respondents are denoted by the 1.0000. 2.000 is marked that type of the persons who respond by the negative view. 9.000 is marked for the not answering cases. At the time of the research, it was found that gender is considered the nominal variable where the male and the female both are used here., Not only this, the age is considering the continuous variables as the age groups are chafing based on the respondent. The marital status is also considering the nominal variables as it is considering the married, unmarried, widow, divorced, separated etc. 

 Chapter 3: Result

3.1 Statistical Analysis

3.1.1 Descriptive Test

The whole study is focused on the different variables where the age of the respondent, sample size, gender and the marital status is included. It took an important part in this research. To know the patterns of the smoking, age groups are needed as it is changed based on the age groups. Not only this, the pattern of smoking is also changed based on the gender. The high rated consumption of the smoker is needed to know the rate of BMI. It is also an important parameter at the time of the analysation. At the time of the analysis, it is found how the pattern of the smoking or the consumption of the alcohol affects the populations. A total number of 1084 participants have been considered in this research. Both male and female participants have been added in this data collection process. Also, their age range varies in a wider range, from 16 years minimum to 97 years maximum. 

1. Socio Demographic Descriptive

Descriptive Statistics
N	Minimum	Maximum	Mean	Std. Deviation
Marital status	1083	1.000	6.000	2.04709	1.435810
Age in years	1084	16.000	97.000	46.58210	18.364467
Whether male or female	1079	1.000	2.000	1.52178	.499757
smoking status	1082	1.00	5.00	2.1691	1.37711
Body Mass Index	1054	16.066	50.453	25.66168	4.448017
Systolic BP (mean 2nd/3rd)	1084	100.000	240.000	136.56273	20.546206
Diastolic BP (mean 2nd/3rd)	1084	39.000	134.000	74.56181	12.707842
Alchol consumption grouped (units) - men	519	1.000	8.000	4.75915	1.567586
Alcohol consumption groupes (units) women	564	1.000	8.000	4.04078	1.414253
Cholesterol levels - grouped	900	1.000	4.000	2.04778	.876682
Extended smoking status	1082	1.000	11.000	3.92791	3.535518
Economic activity status	1077	1.000	8.000	3.27669	2.520832
Glycosylated haemoglobin result	878	4.700	17.000	6.50524	1.215876
Valid N (listwise)	0

Table 1: Socio Demographic Descriptive Status

(Source: IBM-SPSS)

From the above tabular form, it is found that socio-demographic descriptive studies are analyzed.

Statistics
Marital status	smoking status	Whether normally has access to car	Whether receives income support	Whether male or female
N	Valid	1083	1082	1083	1073	1079
	Missing	1	2	1	11	5
Mean		2.04709	2.1691	1.19298	1.87232	1.52178
Median		1.00000	2.0000	1.00000	2.00000	2.00000
Std. Deviation		1.435810	1.37711	.394822	.333888	.499757
Skewness		1.092	.905	1.558	-2.234	-.087
Std. Error of Skewness		.074	.074	.074	.075	.074
Kurtosis		.032	-.534	.428	2.998	-1.996
Std. Error of Kurtosis		.149	.149	.149	.149	.149
Minimum		1.000	1.00	1.000	1.000	1.000
Maximum		6.000	5.00	2.000	2.000	2.000

Table 2: mean and median table for categorical variables (Source 2: IBM SPSS)

Marital status
Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Married	639	58.9	59.0	59.0
	Cohabiting	60	5.5	5.5	64.5
	Single	196	18.1	18.1	82.6
	Widowed	98	9.0	9.0	91.7
	Divorced	62	5.7	5.7	97.4
	Separated	28	2.6	2.6	100.0
	Total	1083	99.9	100.0
Missing	Not answered	1	.1
Total		1084	100.0

smoking status
Frequency	Percent	Valid Percent	Cumulative Percent
Valid	never smoked	494	45.6	45.7	45.7
	ex smoker	252	23.2	23.3	68.9
	light smoker	109	10.1	10.1	79.0
	moderate smoker	113	10.4	10.4	89.5
	heavy smoker	114	10.5	10.5	100.0
	Total	1082	99.8	100.0
Missing	no answer	2	.2
Total		1084	100.0

Whether normally has access to car
Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Yes	874	80.6	80.7	80.7
	No	209	19.3	19.3	100.0
	Total	1083	99.9	100.0
Missing	Not answered	1	.1
Total		1084	100.0

Whether male or female
Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Male	516	47.6	47.8	47.8
	Female	563	51.9	52.2	100.0
	Total	1079	99.5	100.0
Missing	Not applicable	5	.5
Total		1084	100.0

Table 3: Frequency tables for categorical variables

(Source: IBM SPSS)

 3.1.2 Hypothesis Testing

a) Hypothesis 1

H1: There is a link between health and lifestyle to influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

H0: There is no link between health and lifestyle influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

From this statistical analysis, it is found that the “critical value” of the chi square is 0.05. At the time of the analysis of the chi square, it is found that “if the result” is greater than the “critical value”, then it is found that the null hypothesis is accepted. The “critical value” of the chi-square is 0.05. In this analysis, the value of the Pearson chi square is 0.024 which is less than the “critical value”. It means “that the null hypothesis is rejected” [Appendix 21].

From the above table, it is found that the value of the significance is higher than the value of the critical of the chi square. From this view, it is also shown “that the null hypothesis is rejected”. In practical life, it is also found that the consumption of alcohol enhances the level of the cholesterol [Appendix 21].

From the above table, it is found that the value of the significance is higher than the value of the critical of the chi square. From this view, it is also shown “that the null hypothesis is rejected”. In practical life, the consumption of alcohol is dangerous to the health [Appendix 22].

Table 4: Hypothesis testing

(Source: IBM SPSS)

From the above figure, it is clearly described “that the null hypothesis is rejected”. From the hypotheses, it is found that it has an impact on society. There is a link between health and lifestyle to influence the blood pressure level and cardiovascular disease for obtaining the impact on the population. When the lifestyle is changed, then a high level of the alcohol is taken. It has an impact on our health. For this the alternative hypothesis is accepted.

Hypothesis 2

H2: The alcohol consumption and smoking pattern among people can “influence the development of cardiovascular disease in an individual”.

H0: The alcohol consumption and smoking pattern among people cannot “influence the development of cardiovascular disease in an individual”.

From the general analysis it is found that the individuals reported no cardiovascular problem are also having lower tendency to get addicted towards alcohol and smoking. This signifies that there is some lower rate of correlation between smoking and the susceptibility of an individual to get affected by cardiovascular disease (Wang et al. 2021). From this statistical analysis, it is found that the “critical value” of the chi square is 0.05. At the time of the analysis of the chi square, it is found that “if the result” is greater than the “critical value”, then it is found that the null hypothesis is accepted. The “critical value” of the chi-square is 0.05. In this analysis, the value of the Pearson chi square is 0.002 which is less than the “critical value”. It means “that the null hypothesis is rejected” and the alternative hypothesis is accepted [Appendix 23].

Table 5: Chi square test for 2nd hypothesis

(Source: IBM SPSS)

From the 2nd hypothesis testing, it is found that it is also rejected. Alcohol consumption and smoking pattern among people can “influence the development of cardiovascular disease. People try to change their lifestyle, they intake alcohol in high volume. After sometime the pattern of the lifestyles totally changed. Obviously, it can “influence the development of cardiovascular disease” (Li et al. 2020).

It is found that the woman who has the history of cardiovascular disease falls under the category of moderate to high level of alcoholic or smoker. The significance rate in the table also shows that there is a high rate of correlation between these two variables. The significance rate in the table is near to 1. Things get different in the history of cardiovascular disease and are correlated with lifestyle (Kotseva et al. 2019). It is found that for the women participants who have no history of cardiovascular disease also has a lesser tendency to fall under the category of alcoholic or smoker. It is also seen that in this case the rate of significance is also low and sometimes it is below 0.5.

3.1.3 ANOVA Testing

H1: There is a link between health and lifestyle to influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

H0: There is no link between health and lifestyle influence the blood pressure level and cardiovascular disease for obtaining the impact on the population.

The ANOVA analysis is included in this hypothesis as it can compare among the two variables at the same point of view. In this assignment, the considering two variables are: level of the blood pressure and the cardiovascular diseases as both are measured based on the lifestyle.

From the above tabular form, it is found that all of the significant values are 0.00. “It means that the null hypothesis is strictly rejected. It means that the alternative hypothesis is accepted”. As a result, all of the variables are expressed as an equal level. So, all of the parameters are interrelated with each other (Joseph, 2019). When the variable of frequency and intensity activity scale is enhanced then the parameter of the cholesterol level is increasing. It is also related to the GHQ score point [Appendix 25].

3.1.4 Regression Analysis

H3: The Fibrinogen level and BMI rate among people have an impact on cardiovascular disease development.

H0: The Fibrinogen level and BMI rate among people don't have any impact on cardiovascular disease development.

The regression analysis is done among the dependent variables. At the time of the analysation, it is found that the consumption of the alcoholic groups are considering the dependent variables. At the time of this analysis, the constant variables are considered the level of the cholesterol. End of this analysis, it is found that the interest of the topic is whether the chosen variables are effective or not.

From the above tabular form, it is found “that the significant value is lower than the “critical value” of the regression coefficient that is 0.05. It is also focused on the same formula that is if the value of the regression is “higher than the critical value, then the null hypothesis is accepted otherwise the null hypothesis is rejected. from this tabular form, it is clearly defined “that the null hypothesis is rejected” (Nassar, 2019). The regression analysis is done to ensure as well as verify the whole analysis. In this regression analysis, the two variables are the: dependent Variable: Alcohol consumption grouped (units) - men, Predictors: (Constant), Cholesterol levels - grouped [Appendix 26].

The regression plot simply demonstrates there is a significant variation in haemoglobin and other variables impacting cardiovascular health. Inside this circumstance, the significance value is 0.035. This implies that any alteration in the respondents' condition might have a significant impact on the other variables in this study (Kivimäki et al. 2018). It also expressed the null hypothesis[Appendix 27].

 3.1.5 T Test

H2: The alcohol consumption and smoking pattern among people can influence the development of cardiovascular disease in an individual.

H0: The alcohol consumption and smoking pattern among people cannot influence the development of cardiovascular disease in an individual.

Through this type of the test, it is also found that comparisons are needed among the two different groups. This test is directly focused on the gesting of the hypothesis. But this type of the test happens at the time of the same category of the populations.

This T test implies that the result frequency or how many times the result will show the same result. The 95% Confidence Interval of the Difference means for 95% time the test shows repeating the same result. This T test emphasised the fact that cardiovascular conditions among all the participants have been observed rather than of grouping of men and women who consume alcohol regularly. That means alcohol consumption can be a possible reason for disease development but not only the sole cause of cardiovascular problems [Appendix 28]. 

From the above tabular form, it is also checked that all of the significant values are representing the 0. The value of the significance is also representing the rejection of the null hypothesis.

 Chapter 4: Discussion

Discussion and Interpretation of Findings

The importance of lifestyles on the patient's health dealing with heart illness is significant. The fundamental link between lifestyle modifications and cardiovascular problems inside the UK population has generated a problem that's been resolved inside this study work. The total analyses, together with statistical data analysis, have made it simple to examine the trend of cardiovascular events growth amongst various sorts of groups. Individuals, who are non-smokers or frequent smokers, get an alcohol intake habit, fibrinogen level, BMI problems and possess BP concerns, were all included in the diverse population. The observations and evaluation of the acquired results strongly demonstrate that everyone's behavioural patterns tend to lead to the development of heart disease. It is not fully evident that only those who have irregular life cycles only develop cardiac problems, but this research has evidently proven that those people have the higher tendency to develop cardiovascular disease (Pan et al. 2018). The importance of this result is that it has provided a deep insight and idea about cardiac problems among the UK population. This analysis has critically reflected upon the result and the data collection process. The results have shown that more or less there is a connection between lifestyle maintenance and health cardiac conditions.

Following the data analysis, a primary data analysis method was used to obtain data from secondary sources. Smoking habit, alcohol intake, blood pressure rate, BMI rate, and fibrinogen level were among the characteristics linked with secondary analysis data collected among selected sample sizes. These variables were analysed using SPSS software, which is primarily used for statistical data interpretation as well as analysing various demographic correlational impacts in terms of the development of relevant circumstances. This technique was carried out and followed using a rigorous and systematic statistical analysis that comprised the regression model, ANOVA test, chi square test, t test, and descriptive statistics for each variable.

All of the hypothesis tests are set up at the beginning time of the study. From the first hypothesis testing, the null hypothesis is explicitly stated to be rejected. It is discovered that it has an impact on society based on the hypotheses. There is a link between health and lifestyle in terms of influencing blood pressure and cardiovascular disease, as well as the population's impact (Sangani and Rodd 2021) When one's lifestyle changes, a large amount of alcohol is consumed. It has an effect on our well-being. The alternative hypothesis is adopted in this case. The second hypothesis is also rejected, according to the results of the second hypothesis testing. Individuals' alcohol use and smoking habits can have an impact on “the development of cardiovascular disease”. When people are attempting to improve their lifestyle, they consume a large amount of alcohol. After a while, the pattern of people's lives completely changed. Obviously, it has an impact on the progression of cardiovascular disease. The third hypothesis is also rejected, according to the results of the tests. People's fibrinogen levels and BMI rates have an impact on “the development of cardiovascular disease”. When people are attempting to improve their lifestyle, they consume a large amount of alcohol. Weight gain occurs as a result of consuming alcohol, and the BMI rate changes as a result.

The null hypothesis is found to be strictly rejected in the ANOVA analysis. It indicates that the alternative theory has been accepted. As a result, all of the variables have the same level of expression. As a result, all of the parameters are interconnected. The parameter of cholesterol level rises when the variable of frequency and intensity activity scale is increased. It also has something to do with the GHQ score point. The T test is also used to ensure that all of the significant values represent 0. The rejection of the null hypothesis is also represented by the significance value.

From descriptive study, without a lot of confidence, it can be argued that the diversity of the age groups allowed in the research is critical for making the research properly aligned with the social platform. In this example, there is a significant standard deviation (Hameret al. 2020). As a result, the age group studied in the study is extremely diverse. The age group diversity is critical for the research since it will provide a wide range of information about each person's cardiovascular health and lifestyle.

It can be observed that the research has done an excellent job of balancing the gender profiles so that it can offer a more accurate picture of the impact of lifestyle and other external factors on an individual's cardiovascular health. The standard deviation of the finding is quite low, which is to be expected given that the majority of the participants are of binary gender. This suggests that the gender profile's diversity of portfolio is well suited with this social background.

The internal cardiac muscle, as well as the vasculature and valves, are all at risk from hypertension, often known as high blood pressure. The diastolic pressure is around 13. This means that variations in diastolic blood pressure are substantially smaller than variations in systolic blood pressure over time. The error margin in the calculation is also small, showing that the factors are mainly in line with the average value (Shan et al. 2018). This conclusion could be interpreted to mean that the participants who agreed to participate in the study had diabetes or hypertension in the majority of cases.

The frequency distribution was utilised to collect insight into areas that need to be subsequently investigated in order to establish a proper link between cardiac health and drinking. Analysing the statistical distribution tables reveals that the majority of those who accepted to participate in the study drink inside the small to middle range. Aside from that, a significant proportion of individuals develop alcoholism. It has been discovered that the participation group is highly diversified and comprises a large number of persons that exhibit various types of drunkenness and drinking habits. This simplifies the whole approach of examining the relationship between drinking and heart health (Salas-Salvadó et al. 2019). The distribution pattern inside the frequency distribution is pretty straight, and thus the mild of the mean quantity of intake is underlined by the majority of the respondents in a comparable sort of acquaintance. Women were selected because, for almost all of the period, alcohol intake might raise the Lipo-protein, which is primarily prevalent among women.

End of the analysis, it is found that all of the null hypotheses are not approved. For this, all of the tests are carrying significant meaning. The changes of the lifestyle always influence the level of the blood pressure. After changing the lifestyle, it is also focused on the impact of the populations.

Strengths and Limitations

Strength	Limitation
This research is based on primary data resources and therefore the correlational design for conducting this study has made the analytical outcome more appropriate in terms of understanding and evaluating the overall study findings (Hsu, 2018).	The principal limitation of the research is the correlation between the variables which can change according to the general perception of the society. Recently the Human Genome Project suggests that the degree of acceptability of an individual to a cardiovascular disease is highly dependent on the genetic feature (Nyberg et al. 2018). The research hasn't done the analysis on the genetic feature to get the proper idea of the effect that the event of smoking and alcoholism can have.
This selection correlational design will also ensure that each of the variables are separately emphasised and the obtained results have created transparent insight about each variable’s importance in cardiovascular disease development (Virtanen et al. 2018).

 Recommendations and Conclusion

Several recommendations can be suggested in this research-based study. There are:

• Avoiding cigarette smoking or alcohol consumption in an uncontrollable manner. This will reduce the risk of cardiac problems.
• Leading a healthy life cycle including controlled BP measurement and BMI level so that cardiovascular problems could not arise.
• Through general check-up of the body will detect any early development of cardiovascular problems and that can help in the treatment process in an early stage (Liao and Lin, 2018).
• Lastly, overall life pattern maintenance including food consumption and sleep pattern will help in managing the health condition better and will prevent any initiation of cardiac problems to a large extent.

It can be concluded from this research-based study that people who have developed some cardiac or cardiovascular problems have some disruption in their lifestyle maintenance. Alcohol And cigarette smoking patterns have made the situation more critical and this has been observed in this analytical research form collected data. The overall analysis has given the meaning of maintaining a healthy lifestyle and also encourages the UK population to take care of their balance in life for obtaining a healthy and fit life expectancy. 

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