Data Analysis And Interpretation: Impact Of Lifestyle On Cardio-Vascular Health Assignment Sample

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Data Analysis And Interpretation: Impact Of Lifestyle On Cardio-Vascular Health Assignment

Chapter 1: Introduction

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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 foodutilisation 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 analysed 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 the regression 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.

Chapter 3: Result

3.1 Statistical Analysis

3.1.1 Descriptive Test

  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.

In these cases, mainly chosen parameters are: age, marital status of the respondent, gender of the respondent, status of the smoking etc. Among the different statistical analyses, it is found that it is easily identified that the trend of smoking is understandable. At the time of the data analysis, the male and the female participant are also included. At the time of the standard deviation, high values indicate the variables have strong relation among the study or the analysis. Through this, different analysation, it is easily found that the child is affected when their parents are consuming the smoking as well as the alcohol. As a result, their economic activities are also easily identified. It is shown that the consumption of smokers and the alcoholic personas economical aspect is effected after consuming this.

Participant characteristics have been described in this result section. From the sample size of the data collection, several details about the demographic details such as the total number of participants, the male female ratio, related age of all those participants, and some other socio demographic data all about these participants have been achieved. The number of male participants was 516 and the same for females was 563. Among them there were 639 married couples who participated in the survey. Apart from the married participants Cohabiting were 60, the number of single participants were 196, widowed 98, divorced and separated were 62 and 28 respectively. From the tabular form, it is found that the diversity of the data is collected to maintain the quality of the study. At the time of the hypothesis testing, diversified data is helpful.

From the basic analysis it is found that it contains a detailed analysis of the difference in the age of 1,086 participants in research. The histogram provides a detailed idea and gets the main line and the derivation that each one is experiencing in the statistical analyses. It is found that the mean age of the participants who had agreed for the research is 46 years. From this above tabular form, it is found that diversified age groups are participating in this primary data collection. As a result, the standard deviation is high which means that it can spread out. 

Age is the important factor at the time of the research study. A different age group is expressed through different types of the concept. Even though consumers feel more at ease with investigators with something they can empathize with, diversification among investigators aids in the promotion of confidence.

The usage of the statistical analytical data for the analysis of the blood pressure of participants who had participated in the research can provide a better sense regarding the overall damage that a regular Lifestyle consisting of smoking and consumption of alcohol can cause to the cardiovascular health of an individual. From the statistical analysis done by the help of the advanced statistical software SPSS it is found that out of 1084 participants of the research there isn't a tendency of showing high blood pressure.

The smoking status of this descriptive analysis has shown that a total number of 1084 respondents are engaged with smoking habits from lite to moderate to light. Also, the ex-smoking habit people and non-smokers have been interviewed while the data collection process had taken place. The number of non-smokers and ex-smokers was 494 and 252 respectively. Apart from this, the numbers of light, moderate and heavy smokers are 109, 113 and 114 respectively. The valid and cumulative percentages have also been demonstrated there and it shows that from the total number of respondents 2 respondents have not responded clearly about their smoking habit or pattern (Nyberg et al. 2020). It has been plotting the smoking status against the frequency and has found that the number of non-smoking persons is highest in the collected data.

Alcoholism has a great effect on the cardiovascular health of an individual. It is seen that people who have greater tendency to develop alcoholism are also reported to be susceptible to cardiovascular diseases. By analysing the female participants who agreed for the research, a greater Idea regarding the perception of alcoholism and cardiovascular health can be obtained. 

Having some idea regarding the cardiovascular health of the participants prior to the actual control or intervention is highly important (Wuet al. 2019). The table clearly defines that 74% of the total participants of the research have never encountered any cardiovascular issues. Other than this 24% of the total participants have encountered the problem. This Diversity on the participant pool is highly beneficial to gather the overall idea of the impact of the lifestyle on the cardiovascular health of the individual. [Appendix 20]

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 2: 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 3: 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.

c) Hypothesis 3

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.

This chi square test has demonstrated the significance value of pearson chi square test of 0.044, the likelihood ratio is of 0.018 and linear association as 0. The number of participants in each of these tests is 50 and for linear association 1 participant has been considered. (Sisti et al. 2018). 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 24].

Table 4: Chi square test for 3rd hypothesis

(Source: IBM SPSS)

From the 3rd hypothesis testing, it is found that it is also rejected. The Fibrinogen level and BMI rate among people have an impact on cardiovascular disease development. People are trying to change their lifestyle, they intake alcohol in high volume. After intaking the alcohol, the weight is gained, as a result the rate of the BMI is changing.

3.1.3 ANOVA Testing

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

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

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 tests are done based on the three hypotheses. Three 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.

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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