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宝鸡地区80 例结肠癌患者发病危险因素研究
引用本文:孙小莉,曹晓侠,丁晓明,张飞鸣,杨芳霞.宝鸡地区80 例结肠癌患者发病危险因素研究[J].现代生物医学进展,2016,16(23):4505-4507.
作者姓名:孙小莉  曹晓侠  丁晓明  张飞鸣  杨芳霞
作者单位:宝鸡市妇幼保健院内科;陕西中医学院附属医院肿瘤科
摘    要:目的:探讨宝鸡地区结肠癌患者的发病的高风险因素,为减少宝鸡地区结肠癌的发病率和死亡率采取有效措施提供理论依据。方法:对我院收治的80例结肠癌患者的病史资料进行统计分析,通过收集同期入院的非癌结肠疾病患者作为对照资料,对危险因素进行详细对比,通过单因素分析和Logistics回归分析,得出高风险影响因素。结果:流行病学研究表明,结肠癌发病率随着年龄的增加显著上升,且在发病患者中,男性患者显著多于女性患者(P0.05)。而结肠癌的病灶分布部位表明,乙状结肠癌发病率最高;单一风险因素的研究表明,低膳食纤维饮食、糖尿病史、高血压史、结肠癌家族史、以及结肠炎史都显著影响结肠癌的发病率(P0.05);Logistics多因素分析表明低膳食纤维饮食、糖尿病史、高血压史和结肠癌家族史是结肠癌的主要危险因素(P.0.05)。结论:高血压、糖尿病、结肠癌家族病史以及低膳食纤维饮食是宝鸡地区结肠癌患病的主要风险因素。为控制宝鸡地区结肠癌的发病率,需要针对性的对结肠癌高危人群进行理论指导和及时的筛查与对应干预措施。

关 键 词:结肠癌  风险因素  Logistics多因素分析

The Pathogenic Research of 80 Patients with Colorectal Carcinoma in Baoji District
Abstract:Objective:To investigate and analysis the high risk factors of colorectal carcinoma in Baoji District in order to provide a basis for taking effective measures to reduce the morbidity and mortality of colorectal carcinoma in Baoji District.Methods:The clinical data of 80 cases with colorectal carcinoma in our hospital were analyzed,and the non-colorectal carcinoma in the same period were chosen as the control group. The risk factors of colorectal carcinomawere analyzed bysingle factor analysis and Logistics regression.Results:The epidemiology study showed that colorectal carcinoma morbidity were increased by age increasing, the morbidity in male patients were more than female patients (P<0.05). The sigmoid carcinoma morbidity was the highest in colorectal carcinoma distribution parts (P<0.05). The low fiber diet, diabetes history, hypertension history, colon cancer family history and colitis were main risk factors of colorectal carcinoma by Logistics multiple-factor analysis (P<0.05).Conclusion:The high risk factors of colorectal carcinoma are hypertension, diabetes, colon cancer family history and low fiber diet. It is necessary to carry theory instruction, screening and intervention measurement targeted people with high risks of colon cancer.
Keywords:Colorectal Carcinoma  Risk factors  Logistics multiple-factor
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