國小學童健康生活型態與身體質量指數之探討

Abstract

研究背景：肥胖現象日益威脅全世界兒童健康，體重過重或肥胖兒童全球的盛行率逐漸上升，體重過重或肥胖的兒童容易在成年時罹患慢性疾病。肥胖的兒童會導致日後肥胖的成年人，並且慢性病有年輕化趨勢。兒童肥胖與很多因素息息相關，其與父母飲食生活型態之間有直接關係，家庭是兒童健康行為養成的重要關鍵，以家庭為基礎的健康促進及飲食生活型態，有助於兒童健康成長及減少成年期慢性疾病的發展。近年來e化健康醫療科技及應用程式，已廣為運用，包括預防及處置健康問題，也應用於管理健康生活型態中。醫療照護需求增加，加上智慧型行動裝置應用程式(applications，簡稱APPs)，近年來蓬勃發展，許多健康照護APPs類型如雨後春筍般產生，用以輔助醫療照護、疾病情監控、或健康管理，以促進民眾健康及減少醫療資源使用其快速發展的背後，隱藏著許多對使用上的風險及內容是否適合的疑問。證據顯示智慧型手機應用程式，也可有效地改變健康飲食行為；並提供兒童及家庭易讀易理解的衛教及健康訊息，確保健康的行為以及健康結果是重要的醫護職責。 研究目的：在台灣少有針對肥胖兒童而規劃的e化健康促進模式之研究，而本研究運用e化資料蒐集方式，旨在於：(1)描述其個人基本屬性分析、兒童之自覺健康狀態、兒童的健康行為(飲食、身體活動、靜態行為、睡眠)及其兒童的身體測量結果(身體質量指數、腰圍及身體脂肪)為何；(2)驗證兒童健康智慧型手機應用程式和Fitbit應用在兒童健康方面之臨床可行性及普及性；(3)評估這智能手機Fitbit應用程式在鼓勵健康行為和改善肥胖兒童健康狀況方面的實用性。了解及探討兒童的健康行為與BMI等身體測量結果的相關性；針對重要影響因素提供改善學童健康生活型態的方案，進而降低醫療及社會的成本。 研究方法：本研究為量性研究設計，自2017年3月至2017年9月期間，以立意取樣方式，選取北區國民小學，分為網頁和手機組以9~12歲國小學童為對象；運用電子表單Cub Health結構式問卷及健康智慧型手機Fitbit及應用程式平台，進行健康狀態及行為收集。研究資料分析方法乃利用 SPSS 22.0 版統計套裝軟體，進行次數分配表、百分比、平均值、標準差、中位數等描述性統計外，另推論性統計也進行Mann-Whitney U Test、Kruskal-Wallis Test、Wilconxon test 比較前後差異，及以 Spearman's correlation分析變項之相關性。 研究結果：本研究共收集26位國小學童，男女比例約1：1.17。平均年齡為10.77歲，平均身高為144.6公分(SD=8.3)，平均體重為41.1公斤(SD=9.5)，包括有新北市國小18名學童及台北市國小8名學童，健康手錶配戴時間，從21到37天不等，平均3.7±1.22個月；新北市國小平均3.0±0.12個月，台北市國小平均5.4±0.97個月。結果發現9至12歲學童體位過重或肥胖有23.08%，身體質量指數(z = -1.96, p <.0 5)、體脂率( z = -2.01, p < .05)、骨骼肌量(z = -3.11, p < .01) 與腰圍(z = -2.01, p < .05)於性別有顯著差異，男童均大於女童；BMI和體脂率(r = .53, p < .01)、腰圍(r = .89, p < .01)與自覺身材胖瘦(r = .66, p < .01)，達顯著性正相關；健康飲食頻率有不同區域的差異(z = -2.12, p < .05)，新北市學童不健康飲食頻率高於台北市區學童(z = -2.05, p < .05)；體脂率與健康飲食頻率(r = - .66, p < .01) 達顯著性負相關；骨骼肌量與燃燒的卡路里(r = .60, p < .01)達顯著性正相關、與步數(r = .42, p < .05)有正相關；自覺身材胖瘦和腰圍達顯著性正相關(r = .53, p < .01)，與步數呈負相關(r = -.41, p < .05)；體脂率男童高於女童(z = -2.01, p < .05)，10歲以下高於10歲以上學童(z = -2.06, p < .05)，新北市學童高於台北市區學童(z = -2.5, p < .05)。 結論與建議：本研究與過去大多數研究一致，BMI等身體測量結果於性別有顯著差異，這些身體測量結果並與自覺身材胖瘦相關；體脂率與健康飲食頻率達顯著性負相關；骨骼肌量與燃燒的卡路里達顯著性正相關；自覺身材胖瘦和腰圍達顯著性正相關；顯示飲食與運動等健康行為與BMI等身體測量結果相關，希望藉此結果及資料收集方法的分析探討，應用於肥胖防治，提供臨床照護者、學校教育人員及衛教工作者作為e-Health健康管理之參考，教導兒童與家長重視家庭學校環境的影響因素，協助建立兒童健康生活型態，幫助兒童有效控制健康狀態及健康行為進而促進健康；並運用e化調查工具進行護理研究，藉此了解學童的健康生活型態，企能提供其他大樣本慢性疾病兒童e化健康促進計畫之參考。

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.