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The Effectiveness of Physical Exercise to Prevent Gestational Diabetes a Randomized Clinical Controlled Trial

In the United States, the pregnant women who develop gestation diabetes are about 1 to 14 % annually who previously had no experience with any form of diabetes (DeSisto, Kim & Sharma, 2010). Classically it is estimated that one woman in every twenty women will develop gestation diabetes despite the conservative approaches used. The Center for Disease Control and Prevention has reported a rate of between 4.6 and 9.2% prevalence in the United States in 2010 alone. In the year 2007-2008, the prevalence rate was 8.1 % and increased to 8.5% in the following year 2009-2010 (DeSisto, Kim &Sharma, 2010). The rate is alarming despite the fact that it can be prevented using guided physical exercises (Koivusalo et al., 2016).

Gestation diabetes is a condition of high blood sugars to pregnant women who previously had no diabetic condition at all. The actual cause for the increase in not yet established but researchers have sufficed with clues that try to link the situation with placental hormones (Coustan, 2013). As the fetal grow in the uterus, the placenta produces hormones that support the development of the fetus. These hormones are suspected to inhibit insulin, and therefore, pregnant women become constrained in regulating the glucose levels. This blockage leads to high sugar levels in the blood of the mother. When high glucose level crosses the placental barrier, they induce the fetal pancreas to produce more insulin to get rid of the excess glucose (Imam, 2013). This action of the fetal pancreas causes the glucose to get converted into fat. Therefore, the fetus becomes huge, and this might pose a danger to child during delivery, where the shoulders are damaged. The macrosomia baby has difficulties in breathing and is at higher risk of developing diabetic because its system has low blood sugars (Koivusalo et al., 2016).

Several types of research are underway that are trying to evaluate ways of reducing gestational diabetes in pregnant women. Some have focused on dieting and lifestyles. The research that would prove viable is that which aims at burning the excess glucose from the body rather than staffing the body of glucose. Physical exercises burn the excess glucose in the blood for immediate utilization. Therefore, the blood sugar would get lowered to normal (Coustan, 2013). It also stimulates the nutrition exchange between the fetus and placenta thereby facilitating the normal growth of the fetus. Guided physical exercise using a randomized clinical trial with controls group would be undertaken in for this research.

The sample sizes to be employed in the study will get drawn from the population by blinded randomization. The candidate to this study will be chosen randomly from the pregnant women who previously had no diabetes and currently diagnosed with gestation diabetes. Random sampling removes bias in the study and generates more reliable data that can more predictably use to draw a generalization. The study design will pick a small sample of about thirty (30) pregnant women from each trimester category. This sample is manageable and yet easy to get within a very short time and meet the threshold for statistical analysis tools in sample statistics. The survey will only consider and include the participants who are willing. Pregnant women who have any diabetes or have a condition that would compromise the results will get excluded from this study.

The selected pregnant women would be categorized divided into two groups through a randomization process. The two groups will be on the same diet. A test group will get put in a series of physical exercise for a period, and then blood samples get drawn for glucose level testing. The control group will get sedentary lifestyles where they will not be involved in physical exercise. The blood sample will also be drawn simultaneously with the test group and the levels of glucose measured and recorded. The candidates are free to decline participation in the study if they feel awkward. Respect for Participants autonomy at all time during the research study will occur.

After the collection of the data and sorting the one that meets quality level for analysis, the coding process will kick off. The data gathered from the field will get coded for compatibility with statistical tools selected for analysis (Edwards & Lampert, 2014). Editing of the entries will only get done where the discrepancy is evident such as spelling mistake or wrong ticks outside the boxes provided in the response section of the recording sheet. Where possible, a participant will be contacted to clarify an entry to remove ambiguity, which has a potential to generate type one error in the research. In all this process, preservation of the integrity of the raw data will be crucial. The skewing of the data will not get tolerated. Any manipulated information will suffer automatic disqualification from further analysis.

Tabulation of the response will get done for visual analysis such as comparison and calculation of percentages and other measures of central tendency including dispersions and standard deviations. The data will get collated into tables and simple charts for easier referencing and inventory. The coded data will now become subjected to statistical analysis such as student t- test and chi-square distribution to generate inferences that will enable for hypothesis testing. The confidence interval and Z-score value generated will be used to accept or reject the theory underpinned by my objectives. The student t-test distribution is a statistical analysis tool that works best for population samples that are small as in my case and where the population is normally distributed (Merriam & Tisdell, 2015). The chi-square will work best by comparing the frequencies of developing the gestation diabetes in both cases. These tests will work best to create an inference that can be used to generalize the deductions from grounded data obtained in the research study. In making the statistical inference, care will be taken to avoid type two error in our study. Interpretation of the inferences will be backed up by confidence intervals and p-value generated by statistical tools and other techniques that will deem viable.

The data generated from analytical tools will get compared with the standards stipulated for the tools and conclusion will be drawn. The results will be discussed and compared with previous work that has been done on the topic to show the area of similarities and pinpoint the differing outcomes (Merriam & Tisdell, 2015). The limitations of the study will be identified and discussed in broad and the challenges encountered will be counted including any limitations that delayed the investigation in any way. The areas that need further research will get listed as a recommendation for further investigation interrogation. The results obtained, discussion and interpretations will get compiled into a report that will add scientific insight to the pool of knowledge already in the public domain.

References

Coustan, D. R. (2013). Gestational diabetes mellitus. Clinical Chemistry, 59(9), 13

DeSisto CL, Kim SY, Sharma AJ.(2010) Prevalence Estimates of Gestational Diabetes Mellitus in the United States, Pregnancy Risk Assessment Monitoring System (PRAMS), 2007–2010. Prev Chronic Dis 2014; 11:130415. DOI: http://dx.doi.org/10.5888/pcd11.130415

Edwards, J. A., & Lampert, M. D. (2014). Talking data: Transcription and coding in discourse research. Psychology Press.

Imam, K. (2013). Gestational diabetes mellitus. In Diabetes (pp. 24-34). Springer New York.

Koivusalo, S. B., Rönö, K., Klemetti, M. M., Roine, R. P., Lindström, J., Erkkola, M., ... & Andersson, S. (2016). Gestational diabetes mellitus can be prevented by lifestyle intervention: The Finnish Gestational Diabetes Prevention Study (RADIEL). Diabetes Care, 39(1), 24-30.

Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation. John Wiley & Sons.