心肺適能檢測除了可評估體能狀況及評等外，更可作為健康風險篩選之工具，有助於早期偵測及預防篩檢。因此，本研究旨在運用已發展之FITNESSGRAM篩選參照標準檢視臺灣某一大學男大專生代謝症候群風險分佈情況及特性；並旨在檢視常模參照及篩選參照對照結果之異同，以初步檢視其可用性。本研究方法擷取並分析某一大學2018年資料庫中541名18歲臺灣男大專生1600公尺跑走測驗數據。以單因子變異量分析與事後檢定分析三組不同健康風險程度之跑走測驗時間、常模百分位和身體質量指數之差異。結果顯示篩選參照之健康適能區、需要改善區和需要改善且高風險分別有70.3%、13.84%和15.71%。三組不同程度健康風險在各項檢測中皆達顯著性差異。需要改善且高風險的學生有心肺適能表現較差且身體質量指數較高之特性。常模參照則將99.08%男大專生評等為不好和稍差。本研究建議以篩選參照標準來解讀心肺適能可提供更多健康相關風險評估的資訊，但未來研究仍須檢視這些重要因子與評估工具預測能力的可應用性。
The cardiorespiratory fitness (CRF) test can be used to assess physical fitness and fitness ranks. It also can be used as a tool for assessing health risks, may help for early detection and screening prevention. Therefore, the purpose of this study was to use the developed FITNESSGRAM criterion-referenced standard to identify the distribution of different metabolic syndrome risk levels and fitness characteristics in male college students in a university in Taiwan. It also aimed to inspect the difference of fitness ranks results between the normative-referenced standard and criterion-referenced standard for feasibility evaluation. The method we extracted and analyzed one-mile run/walk test data of 541 aged 18 years male Taiwanese college students from the dataset in 2018. One-way ANOVA and post hoc analysis were performed to examine the difference of the duration of 1MRW, the normative percentile, and body mass index (BMI) among three health risk levels. The results showed that there were 70.3%, 13.84%, and 15.71% of students classified into HFZ, NIZ, and NI-health risk, respectively, when using criterion-referenced standards. It had a significant difference between three different health risk groups in all fitness results. The characteristics of lower CRF and higher BMI were marked as a health risk. But it showed 99.08% of colleges were ranked as the poor and the fair when using normative-referenced standards. It suggested that the criterion-referenced standards to interpret CRF could be more informative for health-related risk assessment. But further studies are also needed to identify the major factors and predicted power for application feasibility.
