Try out PMC Labs and tell us what you think. Learn More. The GFL program was deed to increase exercise and educational opportunities, which positively impact health risk factors in Lubbock residents. The GFL program de included the recruitment of subjects to participate on a team that consisted of four individuals, each subject tracked their exercise minutes, and their educational session attendance.
The tracking of exercise and educational sessions was done on the GFL website.
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Biometric testing was conducted pre- and post- intervention. The program was located within the Lubbock community in places that were close to their place of residence. The intervention included walking and educational sessions, including goal setting lectures, nutrition information, and exercise demonstrations.
Study participants, included male and female adults who tracked their exercise time and educational sessions. Exercise minutes and educational session attendance were self-reported. Our data analysis revealed that ificant difference was found between pre- and post- intervention measures, including weight, body mass index BMIhigh-density lipoprotein HDL.
Based on these findings, we conclude that the intervention showed positive effects on exercise and lifestyle. The United States faces an epidemic of unhealthy behaviors. Modifiable risk factors such as obesity, high blood glucose, hypertension, and physical inactivity le to chronic diseases Centers for Disease Control and Prevention. Currently, more than one-third of adults in the U.
Nationally, While in Texas, the statistics reported are even higher at As a nation, the U. As a consequence, because the highest risk factor for developing type-2 diabetes is obesity, the incidence of diabetes has skyrocketed to over 25 million nationwide Centers for Disease Control and Prevention.
National diabetes fact sheet,with over 1. Organizations across the country have been implementing strategies to help combat these dating someone with Lubbock TX disease trends. Strategies range from environmental changes to policy interventions. Environmental changes include increasing opportunities for individuals to use public facilities for increased opportunities.
These include building walking trails at local parks and adding bike lanes and routes to protect individuals that would use active modes of transportation. One of the largest policy interventions is the addition of wellness programs to workplaces.
These programs not only increase the health and morale of employees, they can also lower costs for the business Stokes et al. While these strategies provide goodit stands to reason that communities across the country need to find creative ways to combat these unhealthy trends as a whole.
Program strategies need to persuade the community to become more active and are simplistic enough to replicate in any setting. The GFL is an 8-week community-based competition in which teams of 4 earn points for exercise, weight loss, and attendance at community events can be implemented in both community and workplace settings. Participants register online or via paper registration form. Teams choose to compete in one of three based on the amount of time each team member commits to exercise every week. include: Raider Rookie, each team member commits to exercising min per week; Raider Power, each team member commits to exercising min per week; and Raider Warrior, each team member commits to exercising min per week.
The subjects in this study participated in the GFL program and used the tracking website.
Participation in the research component was entirely optional and did not affect any part of the competition. Teams, as a whole, did not need to partake in the research study.
Lubbock County consists of more thanpeople. Among them the majority is Hispanic or Latino, which comprises Census Bureau 5. Approximately, 33, people are diagnosed with diabetes each year, and 85, are diagnosed with pre-diabetes and Census Bureau; Carr, Based on these statistics, it is apparent that active living opportunities and healthy eating education is needed.
The GFL program was the intervention used in the study. The intervention includes an exercise and educational component. Subjects earn 1 point per minute of exercise, 50 points per each percent of weight loss, and 50 points for attending educational sessions. The teams with the most of points at the end of the 8 weeks won the challenge.
The study aimed to decrease modifiable risk factors of subjects that participated in GFL. The overall goal was to determine how the GFL program impacted subjects' cholesterol levels, glucose levels, blood pressure levels, weight, BMI, and body fat percentage. Educational session attendance was also self-reported. However, in sheets were at each educational session. Therefore, study personnel were able to verify attendance at education sessions.
After final IRB approval of the study, study personnel began recruitment by posting approved fliers in various locations in the community. The primary areas of focus included community centers, senior centers, grocery stores, local businesses, and clinics. Informational sessions were also held at community centers and senior centers.
s with flier attachments and information about the program were distributed to GFL participants.
The community members who were interested in the program, registered online at www. If participants chose to be involved in the research study, the study personnel were alerted of the participant's involvement via s, mails, or telephones. The study personnel then called each participant to confirm their participation and set an appointment to conduct biometric screenings, completion of a consent form, a behavioral survey, and the inclusion and exclusion criterion information sheet. The questionnaire is included in the Appendix.
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There were three deated locations to complete the necessary paper works and have the biometric testing conducted. Study participants had the following tests conducted: lipid panel testing subject's cholesterol and A1C testing subject's blood glucose.
These tests required a h fasting period No food or drink. Water was allowed, and no vigorous exercise for 12 h prior before the blood draw. Other tests included: blood pressure, body mass index BMI and body fat percentage. The study participants were not found to have any abnormal vital s or laboratory during this study according to the UMC Lab Department.
The post-testing of biometric screenings was conducted during the end of the 8th week of the study.
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The post-testing screenings were similar to the initial screenings; testing was not conducted at the MTS and a behavioral survey was not conducted. These tests required a h fasting period no food or drink, water was allowed, and no vigorous exercise for 12 h prior before the blood draw. Our target population was minorities within the Lubbock, West Texas population, which included primarily the African American and Hispanic ethnicity groups within our community.
The sample size was calculated by using G x Power software version 3. This software was used to obtain descriptive and inferential statistics of the variables for the pre and post measurements. Details are given below.
Shows Pre- and Post-interventions measures, including weight, body mass index, high-density lipoprotein. A Represents overall body weight comparisons between pre and post-interventions; B Represents overall body mass index between pre and post-interventions; C Represents overall high density lipoprotein between pre and post-interventions; and D Represents overall glucose comparison between pre and post-interventions.
The age group 21—70 comprises Sixty-nine percent were female and thirty-one percent were male of the participants. Pre- and post- measurements of the participants—descriptive statistics.
The Kolmogorov—Smirnov K-Statstest of normality was used to determine whether each variable for pre and post were normally distributed. We also checked the normality of each variable by Q-Q Quantile-Quantile plots and then used the paired samples t -test for each of the variables. The glucose and systolic blood pressure variables did not meet the normality assumption even though statistical transformation was performed in order to use the paired samples t -test. When running the paired samples t -test, we used the subjects who completed both pre and post measurements.
The test statistic t -value was equal to 3. We conclude there was a ificant difference between pre and post mean weights. The paired t -test for BMI followed, which was transformed for normality by a square root transformation due to some influential observations. We conclude there was a ificant difference between pre and post for BMI measurements.
There was no ificant difference between pre and post mean LDL measurements.