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Objective:To investigate the awareness of diabetes knowledge among the health examination population and its influencing factors.Methods:A cross-sectional study. From september to november 2022, the subjects of six health examination centers located in six different cities (Beijing, Shanghai, Tianjin, Chongqing, Xiamen, Hangzhou) in China were investigated in the form of questionnaires to investigate the awareness of diabetes core information and the level of trust to different information sources of diabetes knowledge. According to the questionnaire results, the subjects were divided into a high awareness group of diabetes core information and a low awareness group. Logistic regression was used to analyze the influencing factors of diabetes core information awareness; the t-test was used to compare the trust degree of the two groups to different information sources. Results:A total of 9 315 people were included in the six centers, including 4 932 men (52.90%) with an average age of (39.36±12.64) years and 4 383 women (47.10%) with a mean age of (37.47±11.85) years. Only 36% of the people had high awareness of diabetes core information; variables such as gender, age, education level, physical examination frequency in the past three years, package price of this physical examination, self-evaluation of diabetes knowledge, diabetes status, and city of residence were variables that affect the level of awareness of core information related to diabetes (all P<0.05). Compared with the low awareness group of diabetes core information, the high awareness group trusted professional medical staff ( t=-9.597, P<0.05) and community health promotion more ( t=-5.014, P<0.05), but did not trust the emerging popular science propaganda means, such as WeChat official accounts/WeChat groups/QQ groups, Internet web page, Tiktok/Kwai and other short video APPs. Conclusion:The awareness rate of diabetes knowledge among the health examination population is low, and it is affected by many factors; Health education on diabetes knowledge should be carried out for people undergoing physical examination.
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In recent years, the pollution problem of particulate matter, especially PM2.5, is becoming more and more serious, which has attracted many people's attention from all over the world. In this paper, a Kalman prediction model combined with cubic spline interpolation is proposed, which is applied to predict the concentration of PM2.5 in the micro-regional environment of campus, and to realize interpolation simulation diagram of concentration of PM2.5 and simulate the spatial distribution of PM2.5. The experiment data are based on the environmental information monitoring system which has been set up by our laboratory. And the predicted and actual values of PM2.5 concentration data have been checked by the way of Wilcoxon signed-rank test. We find that the value of bilateral progressive significance probability was 0.527, which is much greater than the significant level = 0.05. The mean absolute error (MEA) of Kalman prediction model was 1.8 μg/m , the average relative error (MER) was 6%, and the correlation coefficient was 0.87. Thus, the Kalman prediction model has a better effect on the prediction of concentration of PM2.5 than those of the back propagation (BP) prediction and support vector machine (SVM) prediction. In addition, with the combination of Kalman prediction model and the spline interpolation method, the spatial distribution and local pollution characteristics of PM2.5 can be simulated.
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Objective To investigate the prevalence of high urine albumin-to-creatinine ratio (ACR) among health check up population and evaluate the potential predictors for ACR. Methods A cross-sectional study was conducted among health check up population in the Zhongshan Hospital during 2015. Potential participants completed urine ACR test,body mass index (BMI) and blood test. ACR level was divided into two groups according to the K/DOQI recommendation:ACR Group(male:ACR≥17 mg/g;female:≥25 mg/g), Normal Group (male:ACR<17 mg/g;female:ACR<25 mg/g). Univariate and multivariate logistic regression models were performed to evaluate the associations of ACR with potential predictors (including age,sex,over-weight or obesity,hypertension,glucose metabolism disorders, hypertriglyceridemia,hypercholesterolemia,high low HDL-C and hyperuricemia). Result Totally 670 people from the health check up population were screened for ACR test, 54 cases were positive, the prevalence was 8.1％. Age, BMI, waist-to-height ratio, SBP, DBP, blood sugar and uric acid had statistical significance between Normal group and ACR group[Age 47.62 ± 11.29 vs. 53.83 ± 11.93, t=-3.858, P<0.01;BMI (24.05±3.12) kg/m2 vs. (24.94±3.49) kg/m2, t=-1.982, P<0.05;waist-to-height ratio 0.51±0.52 vs. 0.53 ± 0.06, Z=-2.146, P<0.05; SBP (mmHg, 1 mmHg=0.133 kPa) 115.31 ± 15.59 vs. 130.91 ± 23.66, t=-4.755, P<0.01;DBP(mmHg) 72.31 ± 9.16 vs. 80.02 ± 9.81, t=-5.897,P<0.01;blood sugar (mmol/L) 4.64 ± 1.20 vs. 5.57 ± 2.77, t=-2.466, P<0.01;uric acid (μmol/L) 362.99 ± 92.80 vs. 397.76 ± 95.62, t=-2.633, P<0.01]. Age, hypertension, glucose metabolism, HDL reduction were risk factors for urinary albumin/creatinine ratio. In the multivariate logistic regression model, hypertension status was found to be associated with ACR positive [odd ratio (OR): 2.843, 95％ confidence interval [CI, 1.472-5.493, P<0.01], glucose metabolism disorders (OR, 2.132, 95％CI, 1.042-4.365, P<0.05). As the number of risk factors increases, the rate of positive of ACR showed marked increase, comparing persons with no risk factors to those with four or more risk factors , the OR value rose up to 18.281. Conclusion Hypertension and glucose metabolism disorder are risk factors of chronic renal dysfunction. With the increase of risk factors, the rate of positive of ACR was higher. ACR test is recommended routine screening for people over the age of 50.