我們需要預測代謝症候群的其他指標嗎？以風險分數方法檢驗六種生理與生化指標

Do we need additional markers in predicting metabolic syndrome? A risk score approach in testing six physical and biochemical indices

賴筱婷(Shiau-Ting Lai)

指導教授 ： 楊浩然

中山醫學大學/健康管理學院/公共衛生學系碩士班/碩士(2016年)

摘要

研究目的: 本研究利用長期追蹤之大規模「壢新世代」資料，掃瞄多種可能的生化指標（以肝臟及腎臟功能相關的指標，包括GOT、GPT、血中尿酸），並控制重要的人口學變項，以期界定出各種生化指標的關係與重要性。本研究以代謝症候群相關常見血液生化數值作探討。
材料方法: 本研究採前瞻性世代研究，資料來源利用壢新醫院收集之「壢新世代」資料分析。第一次參與總樣本數為5,757人，其中仍舊參與第二次篩檢者為4,639人，其中仍舊參與第三次篩檢者為3,644人，挑選三次都有參與調查的民眾做為本研究樣本數，共計為3,644人。依據我國行政院衛生署之世界衛生組織之成人診斷標準，建議五項危險因子符合三項(含)以上，即可診斷為代謝症候群。進一步將所有生化指標歸類成六大類，分別是身形類(身體質量指數、腰圍)、尿酸類、肝功能(麩草酸轉氨脢、麩丙酮酸轉氨脢)、血脂類(低密度膽固醇、高密度膽固醇、三酸甘油脂、膽固醇)、血糖類、血壓類，之後以廣義線性方程式分析各生化指標對代謝症候群的影響並且使用「風險分數」(risk score) 加總目前這些因子分數的加總去歸類病人在危險分層中的層級。同時，利用接收者操作特徵曲線，比較曲線下方的面積做為模型優劣的指標，利用SAS 9.4版套裝統計軟體進行。
結果: 代謝症候群三期的盛行率以及發生率，第一次盛行率為7.57%；在第二次健檢得病盛行率為10.65%，發生率為7.81%；在第三次得病盛行率為9.93%，發生率為4.48%。
基本人口學與代謝症候群之單變項分析中，結果得知年齡、性別、教育程度、個人收入、抽菸、喝酒和運動次數與代謝症候群有關。在單變項分析，在白血球數、紅血球數、飯前血糖值、膽固醇、三酸甘油脂、低密度膽固醇、收縮壓、舒張壓、體重、腰圍、臀圍、尿酸、麩草酸轉氨脢、麩丙酮酸轉氨脢、高密度膽固醇、身體質量指數、及體脂値都呈現顯著。在相關因素與代謝症候群之多變項分析，再調整完其他變項之後，在生化指標變項上，僅白血球數、飯前血糖值、高密度膽固醇、收縮壓、舒張壓和腰圍呈現顯著。再將六大類分為高低暴露兩組觀察生化值與代謝症候群之分析，結果顯示生化指標六大類均呈現顯著，在高暴露組比起低暴露組得到代謝症候群的風險上依序為腰圍(19.60倍)、身體質量指數(10.58倍)、三酸甘油脂(10.22倍)、血壓(7.46倍)、高密度膽固醇(3.74倍)、飯前血糖值(2.46倍)、尿酸(2.42倍)、麩丙酮酸轉氨脢(2.35倍)、麩草酸轉氨脢(2.18倍)、低密度膽固醇(1.37倍)、膽固醇(1.35倍)。最後分析全部十一個生化指標加總後的危險分數的模式和另外也試著將身體質量指數取代腰圍放入標準訂定的五個危險因子中的危險分數的模式，結果發現仍以原先代謝症候群標準訂定的五個危險因子加總後的危險分數的模式更好。
結論: 我們認為不需要其他的代謝症候群的預測指標，因為分析結果顯示仍以目前現行的代謝症候群標準訂定的五項預測危險因子的模式更好，在代謝症候群的預測上更為合適。但生化指標仍可作為預測代謝症候群的輔助工具。

關鍵字

代謝症候群 ； 身體質量指數 ； 腰圍 ； 尿酸 ； 麩草酸轉氨脢 ； 麩丙酮酸轉氨脢 ； 低密度膽固醇 ； 高密度膽固醇 ； 三酸甘油脂 ； 膽固醇 ； 血糖 ； 血壓 ； 危險分數

並列摘要

Research purposes: In this study, long-term large-scale data tracking, and scan a variety of possible biochemical indicators (related to liver and kidney function indicators, including GOT, GPT, blood uric acid), and controls the important demographic variables, in order to define the importance of the relationship between various biochemical indicators. In this study, the metabolic syndrome associated with common blood biochemical indices for discussion.
Materials and Methods: This study was a prospective cohort study using landseed hospital data collected for analysis. The first people to participate in the number of samples is 5,757, and which are still involved in the second screening was 4,639, and the third of which are still involved in the screening were 3,644, has selected three times as the present study surveyed the number of samples, for a total of 3,644.Adult diagnostic criteria according to Health Promotion Administration, Ministry of Health and Welfare, and five risk factors in line with three (or more), can be diagnosed with metabolic syndrome.
All biochemical indices further classified into six categories, namely the stature (body mass index, waist circumference),Uric acid, Liver function (glutamic-oaa transaminase, glutamic-pyruvic transaminase),Lipids (LDL cholesterol, HDL cholesterol, triglycerides, cholesterol),blood sugar, and blood pressure.
After the generalized linear model to analyze the impact of each biochemical markers of metabolic syndrome and the use of "risk score" (risk score) plus the current total sum of these factors scores to classify the patient level in risk stratification.Meanwhile, using the receiver operating characteristic curve,compare the area under the curve as a model merits indicators.Using SAS version 9.4 statistical software package performed.
Results: The prevalence and incidence of metabolic syndrome, the prevalence was 7.57% for the first time; In the second health examination ,the prevalence was 10.65%, the incidence was 7.81%;In the third health examination ,the prevalence was 9.93%, the incidence was 4.48 percent. Univariate analysis of demographic and metabolic syndrome, the result of that age, gender, education, personal income, smoking, drinking and exercise frequency and metabolic syndrome related.
In univariate analysis, white blood cell count, red blood cell count, fasting blood glucose, cholesterol, triglycerides, LDL cholesterol, systolic blood pressure, diastolic blood pressure, weight, waist circumference, hip measurement, uric acid, glutamic-oaa transaminase, glutamic-pyruvic transaminase, HDL cholesterol, body mass index, and body fat are significant. In multivariate analysis of correlation factors associated with metabolic syndrome adjusting other variables, on the biochemical indexes variables, only the white blood cell count, blood glucose level before meals, HDL cholesterol, systolic blood pressure, diastolic blood pressure and waist circumference presents significant. Then divided into six categories of high and low exposure groups to observe and analyze biochemistry and metabolic syndrome, the results showed that the biochemical indicators in six categories are significant.
The risk of high exposure group compared to the low exposure group on metabolic syndrome are waist circumference (19.60), body mass index (10.58), triglycerides (10.22), blood pressure (7.46), high density lipoprotein cholesterol (3.74),fasting blood glucose(2.46), uric acid (2.42), glutamic-pyruvic transaminase(2.35), glutamic-oaa transaminase(2.18), LDL cholesterol (1.37), and cholesterol (1.35).
Finally, eleven biochemical indexes to add up the risk score model and additionally also tried to replace waist by the body mass index into five risk factors add up to risk score model. It was found that the original five risk factors add up to risk score model is still better.
Conclusion: We do not need other predictors of metabolic syndrome,because the analysis showed that the original five risk factors add up to risk score model is still better,and the prediction of metabolic syndrome is more appropriate.
But biochemical indicators are still as a predictor of metabolic syndrome.

並列關鍵字

Metabolic syndrome ； body mass index ； waist circumference ； uric acid ； glutamic-oaa transaminase ； glutamic-pyruvic transaminase ； LDL cholesterol ； HDL cholesterol ； triglycerides ； cholesterol ； blood sugar ； blood pressure ； risk score

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