過重與非過重青少年之健康行為比較

Comparison of Health-related Behavior between Overweight and Non-overweight Adolescents

背景：青少年體重過重（含肥胖）是可控制之健康問題，青少年過重在台灣和許多已開發國家中是一不可忽視之健康議題。過去許多有關過重之研究，皆強調肥胖的原因來自於基因遺傳和環境的影響，但國內卻鮮少有文獻從居住地區以及生活習慣中採行健康促進行為之頻率來分析影響青少年過重之因素。目的：因此本研究主要目的在探討過重與非過重青少年，其健康相關行為之差異及影響青少年過重之相關因素。方法：本研究採橫斷面及描述性之相關研究設計，以SAS CATMOD進行集群分析與對數線性模型探究影響青少年體型之相關因素。研究對象包含358位非過重與301位過重之青少年。結果：結果顯示非過重青少年傾向屬於健康組，過重青少年傾向較不健康之組別；過重組不但出現缺乏健康相關行為（包括生命欣賞、健康責任、社會支持、壓力處理、健康飲食與規律運動），也出現較常看電視與玩電腦遊戲之時間頻率。對數線性模型顯示看電視時間、居住地區、健康促進行為與體型有直接的相關性；即相較於長時間看電視者，少看電視時間者有1.6倍的機會是屬於非過重組；而居住於鄉村、較常執行健康促進行為者，分別有1.4倍與1.3倍的機會高於其相對比較組而成為非過重者。結論：影響青少年過重之顯著因素為(1)看電視頻率高，(2)居住於都市，(3)較少執行健康促進行為。本研究之發現將可以提供有關青少年過重問題之知識與改善策略之發展。

Background: Excessive weight gain in adolescents is one of the most prevalent and potentially controllable health problems. Adolescent overweight (including obesity) continues to be an important issue for health services in Taiwan and many developed countries. Many researches related to overweight mainly focused on the genetic and environmental determinants regarding the etiology. However, few studies showed factors such as living locations and health promoting lifestyle influenced the condition of overweight. Purpose: This study aims to compare the difference of health-related behavior and associated factors between overweight and non-overweight adolescents in Taiwan. Method: A cross-sectional, descriptive and correlation design was used. Cluster analysis with SAS CATMOD and a log-linear model were applied to explore the associated factors of adolescent body size. Result: Findings showed that 358 non-overweight and 301 overweight adolescents participated in this study. Non-overweight adolescents tend to be the healthy cluster while overweight adolescents tend to be the unhealthy group. The overweight group performs health-related behaviors significantly less frequently than the non-overweight group does (including life appreciation, health responsibility, social support, stress management, nutrition and exercise). The frequencies of TV-watching and playing computer games, associated with less health-promoting behaviors, are obviously higher in the overweight group. The log-linear model suggests that there is a direct association among TV-watching, living location, health-promoting behavior, and body size. The probability of those who watch less TV becoming non-overweight group is 1.6 times relative to those who watch more TV; that of those who live in a rural area relative to those living in an urban area is 1.4 times and those who perform more healthy behaviors is 1.3 times to become non-overweight group. Conclusions: The strongest factors associated with overweight are (1) an increasing frequency of TV watching, (2) living in an urban area, and (3) few health-promoting behaviors. These findings could be used to further develop and refine the knowledge and strategies for the management on overweight adolescents.