本文選題：2型糖尿病 + 多代謝異常��； 參考：《鄭州大學》2016年碩士論文

【摘要】：2013年,中國糖尿病的患病人數(shù)為9840萬例,居全球首位,糖尿病[其中90%以上是2型糖尿病(type 2 diabetes mellitus,T2DM)]已經(jīng)成為中國一個重大的公共衛(wèi)生問題。多代謝異常是指超重或肥胖、高血壓、高血糖、血脂異常等多代謝異常組分的個體聚集情況,可顯著增加T2DM的發(fā)病風險。因此,有效地檢出和控制與T2DM相關的危險因素,篩查T2DM高危人群,是預防控制T2DM的重要措施。目的1.基線多代謝異常各組分與T2DM發(fā)病風險的關系。2.基線體質指數(shù)(body mass index,BMI)、腰圍(waist circumference,WC)與腰身比(waist-to-height ratio,WHtR)的組合與T2DM發(fā)病風險的關系。3.基線多代謝異常的聚集與T2DM發(fā)病風險的關系。4.多代謝異常基線和隨訪的動態(tài)變化與T2DM發(fā)病風險的關系。方法于2007年7—8月和2008年7—8月選擇河南省新安縣的兩個鄉(xiāng)鎮(zhèn)(磁澗鎮(zhèn)和鐵門鎮(zhèn))為研究現(xiàn)場,以自然村為單位,采用整群抽樣的方法,抽取18歲及以上的居民20194名作為研究對象。研究內容包括問卷調查、體格檢查、空腹血糖及脂質譜檢測。2013年7—8月和2014年7—10月對這些研究對象進行相同研究內容的隨訪,共隨訪到17265名(應答率為85.50%),最終11718名(男性4426名,女性7292名)研究對象被納入本研究。應用發(fā)病密度及Cox比例風險回歸模型對多代謝異常與T2DM發(fā)病風險的關系進行分析研究。結果1.11718名研究對象中,男性4426名,女性7292名,平均隨訪時間為6.01年,共計70016.18人年。隨訪期間新發(fā)T2DM 677例(男性254例,女性423例),發(fā)病密度為9.67/1000人年(男性為9.52/1000人年、女性為9.76/1000人年)。2.基線多代謝異常各組分及其聚集以及基線BMI、WC與WHtR的組合與t2dm發(fā)病風險的關系:(1)調整基線時性別、年齡、吸煙、飲酒、糖尿病家族史后,bmi超重組、bmi肥胖組以及wc、whtr、收縮壓(systolicbloodpressure,sbp)、舒張壓(diastolicbloodpressure,dbp)、空腹血糖(fastingplasmaglucose,fpg)、總膽固醇(totalcholesterol,tc)、甘油三酯(triglyceride,tg)、高密度脂蛋白膽固醇(highdensitylipoprotein-cholesterol,hdl-c)異常組人群的t2dm發(fā)病風險分別高于相應指標正常組人群,其hr(95%ci)分別為2.28(1.83-2.84)、4.78(3.80-6.01)、3.00(2.47-3.65)、3.37(2.68-4.22)、1.56(1.27-1.92)、1.68(1.37-2.06)、9.10(7.61-10.89)、2.10(1.49-2.96)、2.83(2.36-3.39)、1.52(1.28-1.82),且fpg異常組人群的t2dm發(fā)病風險最高。(2)調整基線時性別、年齡、吸煙、飲酒、糖尿病家族史后,以bmi正常且whtr正常組為參照,無論bmi正常與否,whtr異常人群的t2dm發(fā)病風險均有所增加,bmi正常且whtr異常組、bmi異常且whtr異常組的hr(95%ci)分別為1.80(1.27-2.56)、3.79(2.99-4.80);同樣調整上述因素之后,以wc正常且whtr正常組為參照,無論wc正常與否,whtr異常人群的t2dm發(fā)病風險均有所增加,wc正常且whtr異常組、wc異常且whtr異常組的hr(95%ci)分別為2.21(1.62-3.00)、3.98(3.14-5.04)。(3)調整基線時性別、年齡、吸煙、飲酒、糖尿病家族史后,以多代謝異常組分聚集個數(shù)0為參照,隨多代謝異常組分[中心性肥胖(wc)、高血壓、空腹血糖受損、血脂異常]聚集個數(shù)由1個逐漸增加到2、3、4個,t2dm發(fā)病風險逐漸增高,hr(95%ci)分別為1.55(1.11-2.18)、4.39(3.20-6.00)、8.68(6.27-12.04)、28.07(19.10-41.26)。3.多代謝異常基線和隨訪的動態(tài)變化與t2dm發(fā)病風險的關系:(1)調整基線時性別、年齡、吸煙、飲酒、糖尿病家族史后,基線wc、whtr、dbp、tc、tg或hdl-c正常組人群中,隨訪轉變?yōu)楫惓５娜巳号c保持正常的人群相比,t2dm發(fā)病風險均有所增加,hr(95%ci)分別為2.28(1.67-3.13)、3.15(2.09-4.74)、1.42(1.07-1.90)、3.19(2.32-4.38)、3.17(2.50-4.03)、1.53(1.20-1.95);基線bmi、wc、whtr、tc或tg異常組人群中,隨訪未控制組人群較隨訪控制組人群t2dm發(fā)病風險高,hr(95%ci)分別為1.47(1.00-2.14)、1.60(1.10-2.33)、1.84(1.20-2.83)、2.22(1.12-4.39)、1.41(1.03-1.93)。(2)調整基線性別、年齡、吸煙、飲酒、糖尿病家族史后,基線血脂正常組人群中,隨訪轉變?yōu)檠惓５娜巳号c血脂保持正常的人群相比,t2dm發(fā)病風險有所增加,hr(95%ci)為2.41(1.83-3.19);基線血脂異常組人群中,隨訪血脂未控制組人群較隨訪血脂控制組人群的t2dm發(fā)病風險高,hr(95%ci)為1.53(1.15-1.99)。結論1.基線多代謝異常各組分異常均可增加T2DM的發(fā)病風險。2.BMI、WC與WHtR三個肥胖測量中,無論基線BMI或者WC正常與否,基線WHtR異常人群的T2DM發(fā)病風險均有所增加。3.隨著基線多代謝異常組分的聚集個數(shù)的增加,T2DM發(fā)病風險逐漸增高。4.無論基線WC、WHt R、TC或TG正常與否,如能有效控制WC、WHtR、TC或TG在正常水平均可降低T2DM的發(fā)病風險。
[Abstract]:In 2013, the number of diabetes in China was 98 million 400 thousand and ranked first in the world. Diabetes [more than 90% of type 2 diabetes (type 2 diabetes mellitus, T2DM)] has become a major public health problem in China. Polymetabolic abnormalities refer to the individual accumulation of multiple metabolic abnormalities, such as overweight or obesity, hypertension, hyperglycemia, and abnormal blood lipid. It can significantly increase the risk of T2DM. Therefore, the effective detection and control of risk factors associated with T2DM and screening of high risk population in T2DM are important measures to prevent and control T2DM. The relationship between the components of 1. baseline multiple metabolic abnormalities and the risk of T2DM is.2. baseline physical index (body mass index, BMI), and the waist circumference (waist circumference,) WC) the relationship with the combination of the waist to waist ratio (waist-to-height ratio, WHtR) and the risk of T2DM; the relationship between the aggregation of multiple metabolic abnormalities and the risk of T2DM incidence in.3. baseline.4., the relationship between the baseline and the dynamic changes of multiple metabolic abnormalities and the risk of T2DM. Methods selected two townships in Xin'an County, Henan, from 7 to August, 2007 and 2008. (magnetic Jian town and tie gate town) for the study site, taking the natural village as a unit, using a cluster sampling method, 20194 people aged 18 and above were selected as the research object. The research contents included questionnaire survey, physical examination, fasting blood glucose and lipid mass spectrometry test for the same research contents in.2013 years from 7 to August and 2014 from 7 to October. A total of 17265 (response rates of 85.50%) were followed up, and the final 11718 subjects (4426 men and 7292 women) were included in this study. The relationship between the incidence of multiple metabolic abnormalities and the risk of T2DM was analyzed with the incidence of incidence density and the Cox proportional hazard regression model. Among 1.11718 subjects, 4426 men and 7292 women. The average follow-up time was 6.01 years, a total of 70016.18 years. During the follow-up period, there were 677 new T2DM cases (male 254, female 423), the incidence density was 9.67/1000 year (male 9.52/1000 year, female 9.76/1000 year),.2. baseline multiple metabolism abnormality components and their aggregation and baseline BMI, WC and WHtR association with the risk of T2DM: (1) After adjusting the baseline sex, age, smoking, drinking, and family history of diabetes, BMI superrecombination, BMI obesity group and WC, WHtR, systolicbloodpressure (SBP), diastolic pressure (diastolicbloodpressure, DBP), fasting blood glucose (fastingplasmaglucose, FPG), total cholesterol (Totalcholesterol, TC), triglyceride (Totalcholesterol, TC), triglycerides, high-density fat eggs The risk of T2DM in highdensitylipoprotein-cholesterol (HDL-C) group was higher than that of the normal group. The HR (95%ci) was 2.28 (1.83-2.84), 4.78 (3.80-6.01), 3 (2.47-3.65), 3.37 (2.68-4.22), 1.56 (1.27-1.92), 1.68 (1.37-2.06), 9.10 (7.61-10.89), 2.10, 2.83 (1.52), 1.52 (1.52). 1.28-1.82), and the risk of T2DM in the FPG abnormal group was the highest. (2) to adjust the baseline sex, age, smoking, drinking, and diabetes family history, with the normal BMI and the normal WHtR group as reference, no matter whether BMI normal or not, the T2DM incidence of abnormal WHtR population increased, BMI normal and WHtR abnormal group, BMI abnormality and WHtR abnormality group. 1.80 (1.27-2.56) and 3.79 (2.99-4.80) respectively. After the same adjustment of the above factors, the risk of T2DM incidence in WHtR abnormal groups increased with normal WC and normal WHtR group, WC normal and WHtR abnormal group, WC abnormal and WHtR exception group were 2.21, 3.98 (3) adjusted baseline. In the history of sex, age, smoking, drinking, and diabetes family history, the number of multiple metabolic abnormalities was 0 as reference. The number of multiple metabolic abnormalities [central obesity (WC), hypertension, impaired fasting blood glucose, dyslipidemia] increased from 1 to 2,3,4, and the risk of T2DM increased gradually, and HR (95%ci) was 1.55 (1.11-2.18), 4.39 (3). .20-6.00), 8.68 (6.27-12.04), 28.07 (19.10-41.26).3. multiple metabolic abnormalities baseline and follow-up dynamic changes associated with the risk of T2DM: (1) adjust the baseline sex, age, smoking, drinking, and diabetes family history, baseline WC, WHtR, DBP, TC, TG, or HDL-C groups, followed by an abnormal population and a normal population. The risk of T2DM was increased, HR (95%ci) was 2.28 (1.67-3.13), 3.15 (2.09-4.74), 1.42 (1.07-1.90), 3.19 (2.32-4.38), 3.17 (2.50-4.03), 1.53 (1.20-1.95), and the baseline of BMI, WC, WHtR, or abnormality was higher in the uncontrolled group than those in the follow-up control group, 1.47 (1.6), 1.6 respectively. 0 (1.10-2.33), 1.84 (1.20-2.83), 2.22 (1.12-4.39), 1.41 (1.03-1.93). (2) adjusted baseline sex, age, smoking, drinking, and diabetes family history, in the baseline blood lipid group, the risk of T2DM was increased, HR (95%ci) was 2.41 (1.83-3.19), and HR (95%ci) was 2.41 (1.83-3.19). Among the abnormal groups, the risk of T2DM was higher in the group of blood lipid uncontrolled groups than those in the blood lipid control group, and HR (95%ci) was 1.53 (1.15-1.99). Conclusion the abnormality of the 1. baseline multiple metabolic abnormalities could increase the risk of T2DM,.2.BMI, WC and WHtR in three obesity measurements, no matter the baseline BMI or WC is normal or not, baseline WHtR abnormality person The risk of T2DM morbidity in the group increased with the increase of the number of.3. in the baseline multiple metabolic abnormalities. The risk of T2DM was increased by.4. regardless of baseline WC, WHt R, TC, or TG, if the risk of WC, WHtR, TC, or at normal levels could be reduced.

【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：R587.1

【相似文獻】

相關期刊論文 前10條

1 曹莉;曹麗娟;;健康管理對2型糖尿病高危個體發(fā)病風險干預效果的評價[J];航空航天醫(yī)學雜志;2011年09期

2 鄧士琳;李愛民;;生活方式與絕經(jīng)后骨質疏松癥發(fā)病風險的關系[J];華中科技大學學報(醫(yī)學版);2009年04期

3 石一鳴;嚴晉華;楊黛稚;鄧洪容;李津;翁建平;;廣東省1型糖尿病患者發(fā)病風險與出生月份的相關性[J];廣東醫(yī)學;2012年18期

4 ;“夜光暴露”增加癌癥發(fā)病風險[J];抗癌之窗;2012年01期

5 周李濤;張穎;陶立波;沈毅;;心血管發(fā)病風險預測模型在降壓療效評價中的應用[J];臨床心血管病雜志;2012年03期

6 Gilham C.;Peto J.;Simpson J.;T.O.B. Eden;張振;;嬰兒期日間護理與兒童期急性淋巴細胞性白血病發(fā)病風險的研究:在英國開展的病例對照研究[J];世界核心醫(yī)學期刊文摘(兒科學分冊);2005年11期

7 孫鳳;陶慶梅;陶秋山;楊興華;曹純鏗;詹思延;;中國臺灣地區(qū)35～74歲健檢人群2型糖尿病患病率以及5年發(fā)病風險預測模型[J];中華疾病控制雜志;2013年05期

8 陳峰;CCl6基因多態(tài)與哮喘病發(fā)病風險的增加相關[J];國外醫(yī)學.遺傳學分冊;1999年06期

9 胡嘉樂;黃婉嫻;高洋;朱安娜;孫敏英;楊學習;;FTO基因單核苷酸多態(tài)性與2型糖尿病發(fā)病風險的相關性研究[J];分子診斷與治療雜志;2013年01期

10 吳松華，項坤三;IDDM診斷和發(fā)病風險預測的進展[J];中華內分泌代謝雜志;1995年04期

相關會議論文 前5條

1 曹麗麗;周瑋;朱研蓓;郭文文;蔡振明;李新秀;朱大龍;王亞平;;hMTH1,hOGG1,MUTYH基因多態(tài)性變異的聯(lián)合作用分析與中國人群2型糖尿病發(fā)病風險關系的研究[A];第十二次全國醫(yī)學遺傳學學術會議論文匯編[C];2014年

2 張倩影;李魁秀;李琰;房朝暉;牛書懷;樊曉妹;宋藏珠;劉紅;;E-鈣粘蛋白基因多態(tài)性與宮頸癌發(fā)病風險關系的研究[A];第五屆全國中醫(yī)藥免疫學術研討會——暨環(huán)境·免疫與腫瘤防治綜合交叉會議論文匯編[C];2009年

3 許曉華;邱曦;金雪立;趙小英;張敏;C.D'Arcy J.Holman;;腌制品與成人白血病發(fā)病風險的病例對照研究[A];2011年浙江省血液病學術年會暨浙江省醫(yī)學會血液病學分會成立50周年慶典論文匯編[C];2011年

4 劉璐;;絕經(jīng)后激素治療與卵巢癌發(fā)病風險[A];第十一屆全國博士生學術年會（生物醫(yī)藥專題）論文集（下冊，墻報P25-P48）[C];2013年

5 吳嘉;汪俊軍;;吸煙與乳腺癌發(fā)病風險的相關性及其生物學機制[A];中華醫(yī)學會第七次全國中青年檢驗醫(yī)學學術會議論文匯編[C];2012年

相關重要報紙文章 前4條

1 曲俊雅;過量食用奶制品增加卵巢癌發(fā)病風險[N];中國婦女報;2006年

2 王樂民;復合雌-孕激素療法列入致癌目錄[N];健康報;2006年

3 編譯 李譯;咖啡可降低前列腺癌發(fā)病風險[N];醫(yī)藥經(jīng)濟報;2009年

4 記者 鄭靈巧;維生素D缺乏增加慢性病發(fā)病風險[N];健康報;2008年

相關博士學位論文 前1條

1 王運紅;神經(jīng)調節(jié)蛋白-1及其受體基因多態(tài)性與心力衰竭發(fā)病風險及預后的關聯(lián)研究[D];北京協(xié)和醫(yī)學院;2016年

相關碩士學位論文 前4條

1 楊香玉;河南省某農村人群多代謝異常與2型糖尿病發(fā)病風險的隊列研究[D];鄭州大學;2016年

2 郭蘭偉;肥胖相關身體測量指標與惡性腫瘤發(fā)病風險的前瞻性隊列研究[D];北京協(xié)和醫(yī)學院;2014年

3 董秀娟;XRCC2、XRCC5基因多態(tài)性與中國北方高發(fā)區(qū)人群食管癌、賁門癌發(fā)病風險的關系[D];河北醫(yī)科大學;2007年

4 楊俊峰;4類植物化學物攝入對乳腺癌發(fā)病風險影響的研究[D];中南大學;2012年

，

本文編號：1842884