Investigating the Relationship between Obesity and Hypertension - Term Paper Example

Investigating the Relationship between Obesity and Hypertension This paper investigates whether the body mass index is associated with hypertension. The sample comprised some 50 out-patient participants systematically drawn from a local hospital. The participants’ heights and weights were recorded and their body mass indexes calculated from them. Their blood pressures were also recorded. The independent variable (blood pressure) was tested for association with the independent variable (body mass index) using the chi square method. It was found that 80% of participants from the obese group had high blood pressure, while 45%, 14% and 0% from the over-weight, normal-weight and under-weight groups respectively had the condition. Body mass index and hypertension were found to be significantly associated. The findings emphasize the need to sustain and invigorate the continuing campaigns against excessive weight gain. Introduction The importance of the Body Mass Index (BMI) has been growing over time. The relevance of this rising importance rests on the awareness created by the many media and community campaigns to stem problems associated with higher BMI measurements. Apparently, higher BMI is associated with many health problems, including hypertension (high blood pressure), obesity, and inactivity. Psychologically, it is understood that most people with such bodily statuses are more likely to have lower self-esteem and experience rejection, which are catalysts for heavy alcoholism and drug misuse as the affected individuals try to get over the rejection and rediscover the lost esteem (Mungreiphy, Kapoor & Sinha, 2011). Even without involving the question of self-esteem, people still retain a healthy consciousness towards BMI for the two most prevalent health problems arising from higher values of the measurement: hypertension and obesity. Basically, BMI is used to classify individuals into obese (BMI index 30 and above), close to obese (overweight) (BMI index 25.0 – 29.9), having normal weight (BMI index 18.5 – 24.9), and being underweight (BMI index below 18.5) (Naik, Dudekula & Reddy, 2012). Studies have shown that higher BMI indexes tend to increase the risk of hypertension. For instance, Mungreiphy, Kapoor and Sinha (2011) found that having higher BMI significantly increased the likelihood of getting hypertension. Similarly, Naik, Dudekula and Reddy (2012) associated higher BMI indexes with hypertension in their study. Based on these simultaneous results from the two research groups above, it is only fair to postulate that higher BMI is a catalyst for hypertension. In the same tone, lower BMI indexes can be associated with better health, including reduced likelihood of getting hypertension. The results above present a conclusive approach for this study. By contrast, the current study will investigate whether BMI is associated with hypertension merely on the basis of the study environment. That is, does the assertion that BMI is associated with the likelihood for hypertension hold for the local community, away from the previously examined populations? Based on this research question, the following hypothesis was developed for investigating the relationship: Null (H0): BMI is significantly associated with the likelihood for hypertension. Alternative (H1): BMI is not significantly associated with the likelihood for hypertension. Methods In order to investigate the relationship between BMI and hypertension, a group of 50 participants will be selected for data collection purposes. The researcher will recruit the participants from the local hospital, from the out-patient department. This is meant to reduce the bias that would otherwise be caused by carrying out a recruitment within the hospital’s in-patient departments, among which are patients admitted for having hypertension. Accordingly, patients will be approached for a one-off assessment of both their BMI and blood pressure levels. As such, the process involved is systematic sampling (Li & Opsomer, 2006), as subjects are approached as they arrive other than using some random criterion. For ethical reasons, the participants will not have any of their personal details (including names, address and contacts) noted. Instead, the participants will be assigned random identities for the sole purpose of the exercise. Due to the brevity of the exercise, in addition to not requiring follow-up meetings with the participants, it is estimated that the response rate will be high, benchmarked at 80%. Therefore, the researcher plans to approach 63 potential participants. The researcher estimates that a power of 0.8 is sufficient for the present study, and intends to employ an alpha level of 0.05. This translates into the indicated sample size, based on an estimated local population of about 1000 people being served by the selected hospital. The BMI is a ratio of the height to weight of the individual. Therefore, the heights and weights of the participants will be recorded together. From these, the corresponding BMIs will be calculated. The blood pressure measurements will also be taken alongside the components of the BMI. Measurements above 140 mmHg are will be treated to be indicative of the presence of hypertension in the respective participants. The blood pressure measurements will be recorded as a scale variable, similar to the BMI index. Individuals will then be classified in accordance with their BMI classifications (underweight, normal, overweight and obese) and their blood pressures recorded against each participant. The dependent variable in this analysis is the blood pressure while the independent variable is the BMI. The analysis will be performed at the 5% level of significance. Data Analysis The analysis will be done using the chi square test. The test has the capacity to establish associations between two or more sets of variables (Michael, 2004). Suitability of the chi square test stems from the ease of cross-tabulating the data to get distinct classes for specific measurements within the sample. In the present case, the BMI will be classified in accordance with the requirement for obtaining results matching to each group associated with a particular weight bracket. This is effective in ensuring that the percentages of respondents matching to each weight category is obtained, and that the overall chi square value and the associated p-value are also obtained. Being a non-parametric test, the chi square test does not rely on the many assumptions that parametric tests such as ANOVA and regression do (Michael, 2004). Therefore, no prerequisite data analysis tests of distribution are required. Results and Conclusion The researcher estimates that 80% of those with BMI higher than 29.9 will be found to have hypertension. The group of overweight individuals is estimated to have a prevalence rate of 45%, while the normal-weight group is estimated to have a hypertension prevalence rate of 14%. Finally, it is estimated that the underweight group has a hypertension prevalence rate of 0%. This is also due to the fact that individuals with such a BMI value are expected to be very few. The chi-square value is expected to be high enough (say 6 and above) to accommodate a p-value less than 0.05 which in turn shows that the test is significant at the 5% level of significance. Consequently, BMI and hypertension are significantly associated. Individuals with higher BMI are more likely to have hypertension while those with lower BMI are less likely to have the condition. These results are, indeed, in tandem with those obtained by Naik, Dudekula and Reddy (2012) and Mungreiphy, Kapoor and Sinha (2011). There is great need to sustain campaigns that educate the populations about the dangers of being overweight as well as offering practical solutions to the continuing problem of excessive weight gain. As noted, excessive weight gain is more likely to place the victim into one of the upper BMI categories, which in turn increases their risk of getting hypertension, not to mention other health and psychological conditions that come with overweight. Therefore, solving the problem of overweight partly also solves the problem of hypertension in the community. References Li, X. & Opsomer, J. D. (2006). Model-based variance estimation for systematic sampling. Washington: ASA. Michael, R. S. (2004). Crosstabulation and chi square. Indianapolis: Indiana University Press. Mungreiphy, N. K., Kapoor, S. & Sinha, R. (2011). Association between BMI, blood pressure, and age: Study among Tangkhul Naga tribal males of Northeast India. Journal of Anthropology. Vol. 2011, Article ID 748147. Naik, J. L., Dudekula, A. B. & Reddy, K. S. N. (2012). Association between body mass index and hypertension: A cross sectional study in an adult male population. Asian Journal of Experimental Biological Sciences. 3(2): 368-377. Read More