BACKGROUND： Intracerebral hemorrhage（ICH） and coronary heart disease （CHD） have the same pathological base, atherosclerosis, and the similar risk factors,such as smoking ,drinking, hypertension, hyperlipemia, dia...BACKGROUND： Intracerebral hemorrhage（ICH） and coronary heart disease （CHD） have the same pathological base, atherosclerosis, and the similar risk factors,such as smoking ,drinking, hypertension, hyperlipemia, diabetes mellitus, etc; but the distributions of two diseases are very different in the populations. This may be related to the exposure of risk factors and different effects of risk factors on two diseases. OBJECTIVE： To analyze the distribution difference of risk factors for ICH and CHD in the populations of Tongliao city of Nei Monggol Autonomous Region. DESIGN： Retrospective analysis. SETTING： School of Radiation Medicine and Public Health, Soochow University; Tongliao Hospital, Nei Monggol Autonomous Region. PARTICIPANTS： Random sampling was used to select 6 hospitals from 10 hospitals affiliated to Tongliao City of Nei Monggol Autonomous Region. Totally 1 672 medical records of patients with ICH and 2 195 medical records of patients with CHD admitted to Department of Neurology and Department of Cardiovascular Internal Medicine of above-mentioned 6 hospitals between January 2003 and December 2005 were collected according to the investigation need. METHODS： The subjects, whose medical records were involved, were performed retrospective analysis with pre-prepared questionnaire ＂Stroke and Coronary Heart Disease Epidemiologic Questionnaire＂. The main contents included： ①Social demography condition： The distributions of gender, age, nationality, etc. ②Previous history of disease： hypertension, diabetes mellitus, etc. ③Related risk factors： systolic blood pressure, diastolic blood pressure, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, smoking, drinking and glucose （GLU）. The database of Epidata was transformed to SPSS database. Single-and multiple-factor non-conditional Logistic regression analysis were performed on the data, and OR value and 95% CI were calculated. The distribution differences of risk factors for two diseases were compared. MAIN OUTCOME MEASURES： Single- and multi-factor non-conditional Logistic regression analysis results of each factor of patients. RESULTS： Single-factor non-conditional Logistic regression analysis showed that statistical significance existed in gender, age, nationality, smoking, drinking, history of hypertension, history of diabetes mellitus, hypertension, triglyceride （TG）, and GLU ten factors（OR =0.199, OR 95% CI 0.142-0.280 to OR =7.484, OR 95% CI 6.186-9.054, P 〈 0.01）. ②The results of multiple-factor non-conditional Logistic regression analysis showed 8 factors including age, gender, smoking, hypertension, history of hypertension, history of diabetes mellitus, GLU and TG（OR =0.203, OR 95% CI 0.114-0.361 to OR =8.262,OR 95% CI 5.466- 12.491, P 〈 0.01）. CONCLUSION： ICH and CHD are the diseases induced by various risk factors. Significant difference exists in gender, age, smoking, hypertension, history of hypertension, GLU, history of diabetes mellitus and TG.展开更多
文摘BACKGROUND： Intracerebral hemorrhage（ICH） and coronary heart disease （CHD） have the same pathological base, atherosclerosis, and the similar risk factors,such as smoking ,drinking, hypertension, hyperlipemia, diabetes mellitus, etc; but the distributions of two diseases are very different in the populations. This may be related to the exposure of risk factors and different effects of risk factors on two diseases. OBJECTIVE： To analyze the distribution difference of risk factors for ICH and CHD in the populations of Tongliao city of Nei Monggol Autonomous Region. DESIGN： Retrospective analysis. SETTING： School of Radiation Medicine and Public Health, Soochow University; Tongliao Hospital, Nei Monggol Autonomous Region. PARTICIPANTS： Random sampling was used to select 6 hospitals from 10 hospitals affiliated to Tongliao City of Nei Monggol Autonomous Region. Totally 1 672 medical records of patients with ICH and 2 195 medical records of patients with CHD admitted to Department of Neurology and Department of Cardiovascular Internal Medicine of above-mentioned 6 hospitals between January 2003 and December 2005 were collected according to the investigation need. METHODS： The subjects, whose medical records were involved, were performed retrospective analysis with pre-prepared questionnaire ＂Stroke and Coronary Heart Disease Epidemiologic Questionnaire＂. The main contents included： ①Social demography condition： The distributions of gender, age, nationality, etc. ②Previous history of disease： hypertension, diabetes mellitus, etc. ③Related risk factors： systolic blood pressure, diastolic blood pressure, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, smoking, drinking and glucose （GLU）. The database of Epidata was transformed to SPSS database. Single-and multiple-factor non-conditional Logistic regression analysis were performed on the data, and OR value and 95% CI were calculated. The distribution differences of risk factors for two diseases were compared. MAIN OUTCOME MEASURES： Single- and multi-factor non-conditional Logistic regression analysis results of each factor of patients. RESULTS： Single-factor non-conditional Logistic regression analysis showed that statistical significance existed in gender, age, nationality, smoking, drinking, history of hypertension, history of diabetes mellitus, hypertension, triglyceride （TG）, and GLU ten factors（OR =0.199, OR 95% CI 0.142-0.280 to OR =7.484, OR 95% CI 6.186-9.054, P 〈 0.01）. ②The results of multiple-factor non-conditional Logistic regression analysis showed 8 factors including age, gender, smoking, hypertension, history of hypertension, history of diabetes mellitus, GLU and TG（OR =0.203, OR 95% CI 0.114-0.361 to OR =8.262,OR 95% CI 5.466- 12.491, P 〈 0.01）. CONCLUSION： ICH and CHD are the diseases induced by various risk factors. Significant difference exists in gender, age, smoking, hypertension, history of hypertension, GLU, history of diabetes mellitus and TG.
