| Summary: | 碩士 === 國立臺灣大學 === 護理學研究所 === 107 === Background: The threat of obesity on children''s health has been increasing, with the increasing prevalence of overweight or obesity in children globally. Children with overweight or obesity are prone to chronic diseases in adulthood. Children with obesity can grow up to adults with obesity in the future, leading chronic diseases that prone to young people. Children with obesity may grow up into adults with obesity in the future, who might develop chronic diseases. Childhood obesity is closely related to many factors; it has a direct relationship with the parents’ eating and lifestyle habits. Family plays an important role in the development of a child''s health behaviors. Family-based health promotion and eating and living patterns can support healthy growth of children and can reduce the development of adulthood chronicity. In recent years, e-health medical technologies and applications have been widely used for prevention and interventions regarding health problems as well as for management of healthy lifestyles. The coupling of increasing medical care demands and smart mobile device applications or apps has flourished in recent years; many types of healthcare apps have been developed for aiding medical care, disease surveillance, and health management. With the rapid development in promoting people''s health and in reducing the use of medical resources, many questions have been raised about the usefulness and risks of these healthcare apps. Evidence shows that smartphone apps can effectively change healthy eating behaviors and provide easy-to-read and easy-to-understand health-related information to children and families; this would ensure development of healthy behaviors and health outcomes are important healthcare responsibilities.
Purposes: A study of e-health promotion models planned for obese children are rarely observed in Taiwan. Methods to collect e-data were used for the following reasons: (1) to describe demographic details, children''s subjective health status, children''s health behaviors (diet, physical activity, static behavior, and sleep), and children''s anthropometric measurements (weight, body mass index[BMI], waist circumference, and body fat percentage); (2) to verify the clinical feasibility and generalizability of the smartphone and Fitbit applications with respect to child health; (3) to evaluate the usefulness of this smartphone and Fitbit application for encouraging healthy behaviors and improving health status of children with obesity. The main focus was to understand and explore the correlation between children''s health behaviors and body measurements, such as BMI. I hoped to provide a reference for collecting health information of school children and to provide solutions for improving lifestyles of school children with respect to important influencing factors; this would result in reduced medical and social economic costs.
Methods: This study was conducted at two elementary schools in the north district of Taiwan from March to September 2017. A valid sample of 26 children aged between 9 and 12 years was recruited to measure health status and behaviors using the electronic form of the Cub Health structured questionnaire, a smartphone application, and a Fitbit smartwatch and application platform. The research data was analyzed using the SPSS 22.0 statistical software package for performing descriptive statistics such as the number distribution, percentage, mean, standard deviation, and median. Inferential statistics were also performed using the Mann-Whitney U test and Kruskal-Wallis test; the Wilconxon test was used to compare the difference between the studied variables pre and after; correlations between the studied variables were determined using Spearman''s correlation.
Results: A total of 26 primary school children aged 9-12 years were enrolled in this study. The boy-to-girl ratio was approximately 1:1.17. Among the children, mean age was 10.77 years (SD = 1.03), average height was 144.6 cm (SD = 8.3), and average weight was 41.1 kg (SD = 9.5). The results showed n 23.08% of the children had overweight or obesity. BMI (z = -1.96, p < .05), body fat percentage (z = -2.01, p < .05), skeletal muscle mass (z = -3.11, p < .01), and waist circumference (z = - 2.01, p < .05) were significantly higher in boys than in girls. BMI and body fat percentage (r = .53, p < .01), waist circumference (r = .89, p < .01) and subjectively perceived fat and thin (r = .66, p < .01), a significant positive correlation. The frequency of healthy eating was significantly different between children living in urban and rural areas (z = -2.12, p < .05); unhealthy eating behaviors were higher among rural children than among urban children(z = -2.05, p < .05). Body fat percentage showed a significant negative correlation with healthy diet (r = -.66, p < .01). Subjective perception of body shape showed a significant positive correlation with waist circumference (r = .53, p < .01), but a negative correlation with the number of steps (r= -.41, p < .05).
Conclusions: The results of this study were consistent with those of most previous studies. Body measurements, such as BMI, differ significantly according to gender. These body measurements are related to conscious perceptions of fatness and thinness; body fat percentage showed a significant negative correlation with healthy diet. Significant positive correlations were observed between skeletal muscle mass and burning of calories and between subjective perception of body shape and waist circumference. This showed that healthy behaviors, such as balanced diets and exercise, are related to body measurements, such as BMI. These results can help in the prevention and treatment of obesity by providing a e-health reference to clinical caregivers, school teachers, and health educators for health management; this may encourage children and parents to pay more attention to factors affecting the home-school environment, help to establish healthy lifestyles for children, and promote health lifestyles by helping children in effectively controlling their health and health behaviors. This feasibility study on e-health data collection can be a valuable reference for other large-scale e-health promotion programs on chronic diseases for children.
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