背景：第二型糖尿病普遍被認為與肥胖相關，隨著全球肥胖率的日益增長，未來糖尿病的盛行率預計將會大幅增加。因此，過重與肥胖是第二型糖尿病的關鍵危險因子之一，除了增加罹病的風險，甚至會引起心血管疾病的併發症。然而，當糖尿病病人確診為糖尿病前，體重或是肥胖持續時間有相當大的差異。而在亞洲地區，儘管過重與肥胖率比起世界其他國家還要低，罹患第二型糖尿病的年紀卻更輕，身體質量指數(BMI)更小，相較之下，亞洲人罹患第二型糖尿病的風險反而高得不成比例。在相似的身體質量指數(BMI)之下，亞洲人的內臟肥胖和中央型肥胖率高於歐洲人，有更高的胰島素阻抗風險。有鑑於第二型糖尿病病人的體重異質性大，且亞洲人在罹病之前可能會表現出與白種人不同的身體質量指數(BMI)軌跡模式，因此本篇研究欲進一步以臺灣資料庫，探討臺灣第二型糖尿病病人在確診前的身體質量指數(BMI)變化，透過了解身體質量指數(BMI)模式的變化，也許可以對於糖尿病流行病學提供新的見解，採取精準公共衛生預防政策。
目的：使用臺灣的資料庫，利用潛在類別軌跡分析(Latent class trajectory analysis），統計分析在最初未有第二型糖尿病的臺灣人，在罹病之前的身體質量指數(BMI)變化模組類別。再 將不同身體質量指數(BMI)模組類別，利用線性混合效應模型(linear mixed-effect model) ，探討腰圍、血壓、空腹血糖和膽固醇等心血管疾病相關危險因子軌跡變化分析。
方法：本研究使用臺灣美兆健康數據資料庫自1996年至2017年的健檢資料，採用巢式病例對照 (nested case-control)研究方式，將發生糖尿病的病例組與非糖尿病個案的對照組以1:4之比例進行發生密度取樣之配對。當收納資料配對完成後，透過潛在類別軌跡分析(latent class trajectory analysis)，分辨識別在第二型糖尿病發病前隨時間推移具有不同身體質量指數(BMI)軌跡模式的分類組別，以評估找尋能夠描述收集資料適合建模的最佳類別分組數。再以此各類別分組數，以線性混合效應模型（linear mixed-effect model）探討分析第二型糖尿病人發病前的身體質量指數(BMI)軌跡變化，以及相關心血管代謝危險因子分析。
結果：將收納資料配對後，分成病例組7,618人與對照組15,316人，再以潛在類別軌跡方法評估病例組分組，可將罹病前的身體質量指數(BMI)軌跡分成三個組別，分別為穩定過重組(stable overweight)，體重增加組(weight gain)和肥胖組(obese)。多數患有第二型糖尿病的人落在穩定過重組(stable overweight) (n=7,016, 92.1 %)，在追蹤年間平均身體質量指數(標準差)為25.1公斤/公尺2(3.2公斤/公尺2)，介於過重與肥胖(24公斤/公尺2 ≤ BMI＜27 公斤/公尺2)之間，體重變化波動不大；而未被診斷第二型糖尿病的對照組，追蹤平均身體質量指數(標準差)則為23.1公斤/公尺2(3.06公斤/公尺2)，體重維持相對穩定，並且保持在參考正常範圍數值。以線性混合效應模型繪製軌跡圖，發現穩定過重組(stable overweight)和對照組在整體上各項指標軌跡上升或下降趨勢相近，而肥胖組(obese)在身體質量指數(BMI)、腰圍、體脂率、空腹血糖、收縮壓、舒張壓和總膽固醇等變項軌跡上與其他組別趨勢較為不同，體重增加組(weight gain)則是在低密度脂蛋白膽固醇(LDL)、高密度脂蛋白膽固醇(HDL)和三酸甘油脂(TG)等變項上與其他組別趨勢較為不同。
結論：本研究是使用糖尿病發生密度配對方式來探討發病前的身體質量指數(BMI)變化，確定了三種不同的身體質量指數(BMI)組別，以了解在糖尿病發病前之身體質量指數(BMI)軌跡變化，發現在發展成第二型糖尿病之前，身體質量指數(BMI)在穩定過重組(stable overweight)為最主要的族群，而非肥胖組(obese)，也許未來在第二型糖尿病的防治方向上，可以著重在更強化整體族群體重的下降。

SUMMARY
Obesity is associated with risk for type 2 diabetes. However, people with diabetes show great variability in terms of BMI, weight gain, and duration of obesity at the time of diagnosis. This study analyzed the data which was retrieved from MJ Health Resource Center between 1996 and 2017 in Taiwan, and used latent class trajectory analysis to model the patterns of BMI in the years before people developed diabetes. There were three different trajectories of BMI patterns identified, including the “stable overweight” group (n = 7,016, 92.1 %), “weight gain” group (n = 333, 4.4 %), and “obese” group (n = 269, 3.5 %). This study also used linear mixed-effect model to examine the mean values of BMI, waist circumference, body fat percentage and other cardiometabolic risk factors such as blood pressure and cholesterol at year 0 and the annual change of these values prior to year 0 for the three identified BMI trajectory classes as well as the control group without type 2 diabetes.

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