This study is aimed to determine the role of smoking and blood sugar level in high blood pressure. In this regard, this report evaluates potential causes of serious health problems such as heart diseases, diabetes and others. It has examined the relationship between demographics like sex, gender and education with blood sugar level, high blood pressure and smoking habits and it has found that there has not any positive correlation addressed between demographics and sugar level as well as high blood pressure. For the present study, the approach of cross-sectional study has found very effective. A sample of 161 participants with age between 18 to 81 years old has addressed appropriately in order to generate appropriate outcomes in the form of self-reporting history about blood pressure, sugar level and smoking habits. making this research relevant for those seeking healthcare dissertation help.
A health risk is termed an element or causes that could increase the chance of developing any kind of disease. As a result of a change in daily lifestyle, smoking is one of the most habits among individuals all over the world. It leads to a variety of health issues in the form of heart disease, cancer and many more. It is responsible for nearly 6.3 million deaths and 6.3% of global DALYs worldwide. (Li et al., 2017). In addition to that, diabetes and blood sugar level are playing a critical role in influencing various risk factors related to the health of people (Poorolajal and et al., 2016). In the context of contemporary human lifestyle, Smoking and diabetes both increase the risk of heart disease in very similar ways, such as an increase in the level of blood pressure. The combination of both factors would increase the chances of a range of chronological diseases such as heart attack or stroke. Because there is random unplanned readmission to the hospital after one month of discharge due to the chronic disease (Jayakody et al., 2018). The present is going to investigate the relationship among different variables of serious health problems that include smoking, blood sugar level and blood pressure. In this regard, this report examines the role of gender on blood sugar level and significant relationship within both factors. For conducting the whole study, the researcher has considered a wide range of health-related statistics for generating appropriate information or research findings. The collection of statistical is performed through a systematic survey.
The study is focused on evaluating different health risk factors that could be termed as important causes of serious health problems such as heart diseases and diabetes. For generating appropriate outcomes, the study has focused on self-reported data of participants that includes information related to high blood sugar level and blood pressure level.
The aim of the study is to examine the role of smoking and blood glucose levels on systolic blood pressure among the resident people in NSW.
As per the aim, some objectives are mentioned below for analysing a wide range of self-reported data so as optimum results could be produced about subject matter:
To determine the relationship between gender and blood sugar level.
To evaluate the relationship between gender and blood pressure.
To analysis the relationship between age and smoking history.
According to Linneberg and et al. (2016), although smoking is a very bad habit, it does not have any impact on the blood pressure levels. They conducted a study on 141,317 participants. The main finding of their study was that there is a casual association of smoking with higher levels of heart rate, but it does not have any connection with the blood pressure levels. Further investigation has determined that an unhealthy lifestyle of people is being addressed as an important cause of health problems such as fluctuations in blood sugar and blood pressure level. In this regard, eating habits, smoking, drugs, alcohol and many more are influencing the blood sugar level, and these factors could produce the additional risk of high blood pressure. On the other hand, Cho and et al. (2015) determined an increase in the number of people suffering from diabetes, who also smoked. They based their study on determining the association between high blood pressure with diabetes. Their sample population included smokers as well as non-smokers. During the study, they found that 1195 smokers experienced an 11% increase in incidences of diabetes.
About 30% of Australian have hypertension, and there is a strong association between high blood pressure (BP) and cardiovascular mortality (Sharman et al., 2015). Sari and et al. (2018) stated that smoking affects glucose metabolism and thus also are among the primary sources for hyperglycemia in diabetes patients. They also found that smoking is also a leading cause of high blood pressure levels. Their study was based on a cross-sectional approach, which consists of 30 diabetic smoking patients and 30 non-smoking diabetic patients. The relevant data were collected through questionnaire-based interviews; while the blood glucose levels were measured through hexokinase and immunoturbidimetry method using cobas 6000 analyser module c501. The results they obtained showed that the fasting blood glucose, postprandial blood glucose and HbA1c increased by 23.64 mg/dl, 58 mg/dl and 0.39% respectively.
In comparison, Li and et al. (2017) focused on analysing the link between smoking and blood pressure in men. Their study was largely cross-sectional in nature. They used systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). The blood pressures were monitored by using digital devices; while the smoking status was determined through the China National Health Survey. They found that the adjusted DBP and MAP were lower in current smokers than in non-smokers. Further, the adjusted SBP was determined to be lower in current smokers as compared to former smokers. They further found that the adjusted blood pressure levels were lower among the current smokers while it was all the higher in non-smokers and former smokers. These results are very different from the ones obtained by Sharman and et al. (2015).
As per the aim and nature of the present investigation, a cross-sectional study is performed by considering different tools and reports such as self-help report and information acquired directly through participants. With the help of a cross-sectional study, the researcher is able to generate appropriate outcomes to study’s objectives. In this regards, some important elements of research methodology are listed below:
In the context of the present investigation, a cross-sectional survey undertaken in 2017at NSW. In this regards, different variables were determined for controlling the process of data collection that played a critical role in deterring the link and relationship among different factors for generating appropriate research outcomes (Kumar, 2019).
With reference to research goals, the researcher hired an external agency that supported the researcher to disclose the participants about the nature of the study and the role of a participant in the study. In this regards, the researcher set up an outlet within a social event or fair to assess volunteer participation of people in the present study.
In the context of the present investigation, both primary and secondary sources of information were considered by the investigator. A survey and direct measures were taken between 10:00 AM to 1:00 PM and it had found very effective for collecting primary data. Therefore the survey was identified as a great primary source in the present study (Silverman, 2016). In this process, a health professional evaluated blood pressure and blood sugar to determine the relationship between different variables. The self-report survey found very effective for assessing the participant’s smoking habits, information related to high blood pressure along with the history of high blood sugar levels. The self-report survey had helped the researcher for determining the relationship between different variables with reference to age, sex as well as highest educational.
Aneroid and digital sphygmomanometer was being used by a professional to measure blood pressure. Regarding the reliability of these instruments, Shahbabu, Dasgupta, Sarkar, Sahoo, & JCDR, 2016, reported that aneroid device is better accuracy than the digital device. A glucometer carried out to determine blood glucose levels. Regarding the reliability of this instrument, Salacinski et al., 2014 suggest that the portable glucometers should be used for patient management, but not for the diagnosis, treatment, or research purposes. The evaluation of this data was being performed with reference to ideal rates. However, the researcher considered different secondary sources such as online books, journals and internet based articles for conducting a literature review in order to gain an in-depth understanding of the topic of investigation.
It is termed as the most important element of each study. In the context of the present investigation, the researcher carried out t-tests for regulating an appropriate comparison of different means (Ledford and Gast, 2018). A chi-square test found very effective for evaluating the link and relationship between categorical variables to generate reliable results.
All the government regulations and norms were considered by the researcher for completion of study under the ethical norms. The review board of the university provided the final approval for the whole plan. In addition to that researcher took formal approval from participants while taking their personal information survey.
Table 1 is showing the mean BGL of male and female participants. The mean value of Female and male BGL is respectively 6.11 and 6.24. Therefore, there is a very little difference addressed in BGL of both gender, but Female BGL is comparatively low. Furthermore, Table 2 shows the calculation of variance analysis and has determined that difference variance is to statistically nonsignificant (t = -358, n.s.).
The above analysis is focused on the analysis of the difference in blood pressure history based on gender. In this context, Table 3 evaluates the proportion of male and female participants who have disclosed their blood pressure history in which 20 female participants and 40 male participants have accepted that they have any kind of blood pressure history. This information determines the history of female in blood pressure is significantly lower than male. In this regards, Table 4 has performed chi-square test for analysing whether the difference is statistically significant or not and this test has determined a borderline difference (X2=3.542, p<0.10) which is lower than alpha value =0.05 criteria for assessing the implication of evidence or significant effect.
As per the above statistic, the analysis of the relationship between age and smoking history is performed. In this regards, Table 5 determines a little difference in the mean age of smokers and non-smokers. The mean age of smokers and non-smokers is respectively 44.20 and 43.66.
Further analysis is focused on conducting the test of statistical significant through variance analysis. In this regards, Table 6 evaluates that age is not having any significant impact on self-reporting smoking history because of the value T= -0.203.
As per the above table, the mean age of the participant is 43.813. The mean value of blood pressure level is 127.143 with Standard deviation of 17.2588. The mean of blood sugar level is respectively 6.186.
The above table is showing a proportion of participants based on gender that is respectively 42.9% of female and 57.1% of male.
As per the above data, it has found that the majority of participants are having appropriate education and have done bachelor. Furthermore, 29% of individuals have done a master’s in education, and 19.1% have done higher secondary.
The above data is showing the 60 out 161 participants are having blood pressure history, and 101 individuals are not having any kind of blood pressure history.
As per Table 11, it has found that 57 out of total participants are having some blood sugar history, and the remaining 104 participants are not having any kind of blood sugar history.
The above Table 12 has determined that 70.8% of participants are not involved in smoking, and only 29.2% are involved in smoking. This information is essential for determining the relationship between different variables.
The present is aimed to determine the relationship among different indicators of serious health problems such as heart disease and others. In this regard, the present investigation paid significant attention to different variables such as age, sex, blood sugar, smoking and blood pressure (Franklin and et al., 2015). By using data associated with self-report survey and blood sugar level of different participants, the present investigation did not find any significant relationship between gender and blood sugar level. This is in contradiction to the results obtained by Li and et al. (2017). They had determined that smoking among men is one of the primary causes of increased blood pressure and sugar levels. They further stated that it is considered as the main reason for increased cases of high blood pressure among men than in women.
Poorolaja and Babaee (2016) argued that unhealthy eating habits and lifestyle of people played a critical role for influencing the blood sugar level because lack of healthy food and lack of physical activities increased the chances of obesity and improper blood sugar level. Therefore, it found that the gender of people could not create any significant image on the blood sugar level. In a similar way, there was not any relationship addressed between self-reported blood pressure history and gender along with age group. Furthermore, there was not any significant correlated identified between age and smoking history. However, the results obtained by Cho and et al. (2015) are very contradictory as they show that men with the habit of smoking are generally more prone to diseases such as high blood pressure and blood sugar levels. On this basis, it can also be stated that the current results match the findings of Linneberg and et al. (2016) and Sari and et al. (2018).
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