ABSTRACT
Purpose@#To evaluate the effect of a gymnastics program for eight weeks to maintain better body composition and decrease fatigue among factory workers. @*Methods@#Data were collected in 54 female workers in their 50s and 60s in a factory located in the S city of the K region between April and July in 2019. The subjects were divided into two groups: 1) experimental group (n=27) received a 30 minute-gymnastics program three times per week, and 2) control group participated in lecture series about the principle and effect of the gymnastics program. Body composition and fatigue levels were measured before and after the intervention and analyzed using the SPSS 23.0 program. To evaluate the differences in demographic and clinical characteristics between the experimental and control groups, the chi-squared test and the t-test were used. Repeated measures two-way ANOVA was performed to evaluate the change between outcomes of the pre-and post-investigation. Pairwise comparisons were used to assess the differences between the groups and the time. @*Results@#There are statistically significant differences in body fat mass (p<.001), body fat percentage (p<.001), basal metabolic rate (p<.001), and body mass index (p<.022) in the experimental group compared to the control group. In particular, there is a significant interaction between the groups and the time in body fat mass (F=6.308, p=.015), basal metabolic rate (F=11.397, p=.001), fatigue (F=6.933, p=.011). @*Conclusion@#Our findings suggest that using the gymnastics program helps women in their 50s and 60s who work in factories promote better body composition and reduce fatigue levels.
ABSTRACT
PURPOSE@#This study aims to provide preliminary data for weight management, and prevention and management of cardiovascular and cerebrovascular diseases. We examined the effect of changes in the weight of workers at a manufacturing company over three years on their metabolic syndrome and metabolic syndrome diagnosis components.@*METHODS@#Necessary data were collected from the questionnaire and the results of the Korean National Health Screening of 2015 and 2017, which included 228 workers at a manufacturing company in G region. The collected data were analyzed using the SPSS/WIN 23.0 program. ANCOVA was used to examine the differences in the metabolic syndrome diagnosis components according to weight change. In addition, multiple logistic regression analysis was used to obtain the odds ratios of metabolic syndrome and metabolic syndrome analysis component, based on the weight changes in the normal weight group and the obesity group.@*RESULTS@#Waist measure, systolic blood pressure, and blood pressure were found to have significant effects based on participants' weight change over three years. These factors increased with a larger increase in weight at a statistically significant level. This study analyzed the weight changes of the normal weight group and the obesity group considering the data from the National Health Screening of 2015, and found that the risk of metabolic syndrome increased at a statistically significant level as body weight increased; thus, the obesity group showed a higher risk in this regard. It was also found that waist measure, fasting blood sugar, and high-density low cholesterol increased at a statistically significant level as body weight increased.@*CONCLUSION@#Health administrators need to recognize the importance of workers' weight management, select an intensive management group based on a time series analysis of weight changes, and develop and implement programs to manage the metabolic syndrome diagnosis components.
ABSTRACT
PURPOSE: This study aims to provide preliminary data for weight management, and prevention and management of cardiovascular and cerebrovascular diseases. We examined the effect of changes in the weight of workers at a manufacturing company over three years on their metabolic syndrome and metabolic syndrome diagnosis components.METHODS: Necessary data were collected from the questionnaire and the results of the Korean National Health Screening of 2015 and 2017, which included 228 workers at a manufacturing company in G region. The collected data were analyzed using the SPSS/WIN 23.0 program. ANCOVA was used to examine the differences in the metabolic syndrome diagnosis components according to weight change. In addition, multiple logistic regression analysis was used to obtain the odds ratios of metabolic syndrome and metabolic syndrome analysis component, based on the weight changes in the normal weight group and the obesity group.RESULTS: Waist measure, systolic blood pressure, and blood pressure were found to have significant effects based on participants' weight change over three years. These factors increased with a larger increase in weight at a statistically significant level. This study analyzed the weight changes of the normal weight group and the obesity group considering the data from the National Health Screening of 2015, and found that the risk of metabolic syndrome increased at a statistically significant level as body weight increased; thus, the obesity group showed a higher risk in this regard. It was also found that waist measure, fasting blood sugar, and high-density low cholesterol increased at a statistically significant level as body weight increased.CONCLUSION: Health administrators need to recognize the importance of workers' weight management, select an intensive management group based on a time series analysis of weight changes, and develop and implement programs to manage the metabolic syndrome diagnosis components.