Effect of Activity Tracker &amp; Application Use on Adherence, Metabolic Syndrome Factor and Body Composition in Middle and Senior-Aged

Kim, Dong Jin; Kim, Min Su; Park, Na Young; Lee, Su Geol; Lee, Yeon Kyung

doi:10.15758/ajk.2018.20.2.28

Cited by 7 publications

(6 citation statements)

References 14 publications

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“…Thus, by recommending appropriate mobile apps and wearable devices and encouraging their use, this study made it possible for the users to engage in sustained health management. The findings of this study align with those from previous studies that revealed the significance of health trackers and smart apps that are free of time and space limitations for a sustained increase in physical activities [ 30 , 48 ]. Previous recommendation systems were rather one-sided and manager-centered, which made it difficult for users to stay entertained.…”

Section: Discussionsupporting

confidence: 90%

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Lee

Kang

2020

J Med Internet Res

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Background The health behaviors of young adults lag behind those of other age groups, and active health management is needed to improve health behaviors and prevent chronic diseases. In addition, developing good lifestyle habits earlier in life could reduce the risk of metabolic syndrome (MetS) later on. Objective The aim of this study is to investigate the effects of the e-Motivate4Change program, for which health apps and wearable devices were selected based on user needs. The program was developed for the prevention and management of MetS in young adults. Methods This experimental study used a nonequivalent control group. In total, 59 students from 2 universities in Daegu, Korea participated in the study (experimental group n=30; control group n=29). Data were collected over 4 months, from June 1 to September 30, 2018. The experimental group received a 12-week e-Motivate4Change program intervention, and the control group received MetS education and booklets without the e-Motivate4Change program intervention. Results After the program, the experimental group had significantly higher scores for health-related lifestyle (t=3.86; P<.001) and self-efficacy (t=6.00; P<.001) than did the control group. Concerning BMI, there were significant effects by group (F=1.01; P<.001) and for the group × time interaction (F=4.71; P=.034). Concerning cholesterol, there were significant main effects for group (F=4.32; P=.042) and time (F=9.73; P<.001). Conclusions The e-Motivate4Change program effectively improved participants’ health-related lifestyle scores and self-efficacy, and significantly reduced their BMI and cholesterol levels. The program can be used to identify and prevent MetS among young adults.

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Section: Discussionsupporting

confidence: 90%

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Lee

Kang

2020

J Med Internet Res

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“…Continuously checking the user’s amount of activity by using activity- and smartphone-based applications can be considered as a measure of confirming the effectiveness of lifestyle and health care. Jee (2017) reported applications to be effective in promoting motivation, and Kim et al (2018) reported that when using activity measurement and smart-based applications to maintain regular physical activity for 23 weeks, 90.65% of males and 91.37% of females showed continuity. The use of mobile devices has a positive effect on self-efficacy by increasing the practice rate of exercising, which is considered to be the factor that can promote continuous participation in exercise.…”

Section: Discussionmentioning

confidence: 99%

Effects of exercise using a mobile device on cardiopulmonary function, metabolic risk factors, and self-efficacy in obese women

Kim

2018

J Exerc Rehabil

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The purpose of this study was to determine the effects of a 12-week walking exercise using a mobile device on cardiopulmonary function, metabolic risk factors, and self-efficacy in obese middle-aged women. For this study, 14 middle-aged subjects with obesity were included and performed walking exercise of 50%–60% maximum oxygen uptake intensity 3 times a week for 12 weeks. As a result, weight, % body fat, body mass index, and waist circumference significantly reduced. In addition, systolic blood pressure, diastolic blood pressure, mean arterial pressure, and hemoglobin A1c significantly reduced, while high-density lipoprotein cholesterol and flexibility significantly increased. Furthermore, exercise using a mobile device significantly increased self-efficacy. In conclusion, walking exercise using a mobile device is a good method to constantly increase the exercise participation rate, as it improves metabolic risk factor and obesity index, and increases self-efficacy.

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“…According to this research, there were no significant statistic difference in blood pressure and fasting plasma glucose, but plasma triglyceride of LPAG was higher than HPAG, and HDL-C of HPAG was higher than LPAG. Lee et al [18][19][20] showed that HPAG had positively affect to the risk factors The advanced research about alcohol consumption showed that HDL-C of high drinking group was significantly lower than moderate drinking group, and fasting plasma glucose, blood pressure, plasma triglyceride, and waist circumference were high enough in high group [24]. In this study, all of fasting plasma glucose, blood pressure, HDL-C, plasma triglyceride, and waist circumference in high group were much higher than those in low group.…”

Section: Discussionmentioning

confidence: 99%

National Health Examination Metabolic Syndrome Item and Health Behavior Analysis

2020

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OBJECTIVES The purpose of this study is to investigate the relationship between the habits of physical activities in several intensities, drinking, and smoking of the general public who live in the S city and diabetes, high blood pressure, high-density lipoprotein cholesterol, plasma triglyceride, and waist circumference of them.METHODS For research, residents of 2,438,370 in S city were selected by using the big data of health checkups sheets that were conducted by the National Health Insurance Corporation in 2017. Physical activities were classified into three groups by intensity. The part of drinking was divided into three groups of non-alcohol, low, and high-drinking people. There were four groups in smoking of non-smoking, the group that smoke lower than the half pack of cigarettes per day, the half to one pack, and more than one pack. Metabolic syndrome frequency analysis and logistic regression analysis were used for this research.RESULTS Compared to the low-intensity physical activity group, the high-intensity group had 0.992, 0.954, 0.871, 0.83, and 0.878 times of lower risk in fasting plasma glucose, blood pressure, high density lipoprotein (HDL-C), plasma triglycerides, and abnormal waist circumference. High drinking group had more risk of fasting plasma glucose, blood pressure, HDL-C, plasma triglyceride, and abnormal waist circumference by 1.326, 1.894, 1.334, 2.125 and 1.263 times than non-drinking group. The group who smoked more than one pack a day had more risk of fasting plasma glucose, blood pressure, HDL-C, plasma triglyceride, and abnormal waist circumference by 1.971, 1.225, 3.229, 2.871, and 1.522 times than the group of non-smoking.CONCLUSION The subjects who did not have risk factors for metabolic syndrome were 29.7%. The average of patients with metabolic syndrome was 25.2%, of which males were 30.3%, and females were 20.1% of them. Metabolic syndrome factors were proved statistically valid. In the physical activity group, the high-intensity physical activity group had a lower risk of metabolic syndrome factors than the low and medium-intensity physical activity groups. The high-drinking group had a higher risk of metabolic syndrome in triglycerides, and the smoking group who smoked more than one pack per day had a higher risk of metabolic syndrome in high-density lipoprotein cholesterol.

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Effect of Activity Tracker & Application Use on Adherence, Metabolic Syndrome Factor and Body Composition in Middle and Senior-Aged

Cited by 7 publications

References 14 publications

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Effects of exercise using a mobile device on cardiopulmonary function, metabolic risk factors, and self-efficacy in obese women

National Health Examination Metabolic Syndrome Item and Health Behavior Analysis

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