1.Correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population
Dianhua DU ; Chunwei WU ; Lan MO ; Xuelin ZHANG ; Wen WU ; Yiping WANG ; Xian WU ; Bo WANG ; Shaohui FENG
Chinese Journal of Health Management 2025;19(4):286-291
Objective:To analyze the correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population.Methods:It was a cross-sectional analysis that employed a simple random sampling method to select 3 496 individuals who underwent healthy physical examinations and cerebrovascular function tests at the Physical Examination Center of the Affiliated Hospital of Guizhou Medical University from January to December 2022. The general information, physical examination data, biochemical examination results, human component analyses, and cerebrovascular function integral data were collected. Based on cerebrovascular function scores, the participants were divided into high-risk group (0-24 points, 70 cases), medium-risk group (25-49 points, 317 cases), low-risk group (50-74 points, 787 cases), and normal group (≥75 points, 2 322 cases). Spearman correlation analysis and receiver operating characteristic (ROC) curve analyses were utilized to assess the correlation and predictive value of obesity measurement indicators and cerebrovascular function integrals.Results:Among the 3 496 subjects included in the analysis, 2 018 were male and 1 478 were female, with an average age of (46.4±7.9) years. The age, systolic blood pressure, diastolic blood pressure, body mass index, waist-to-hip ratio, body fat ratio, body fat content, visceral fat area, fasting blood glucose, total cholesterol, low-density lipoprotein, homocysteine all exhibited an increasing trend as the cerebrovascular function integral value decreased (all P<0.05). The skeletal muscle content in the low-risk group was significantly higher than those in the high-risk group, medium-risk group, and normal group [45.00 (36.80, 50.60) vs 44.10 (36.98, 50.45), 44.50 (37.80, 50.20), and 42.75 (36.30, 48.60) kg, respectively] ( P<0.05). The triglyceride level in the medium-risk group was higher when compared to those in the high-risk group, low-risk group, and normal group[1.87 (1.29, 2.70) vs 1.71 (1.24, 2.80), 1.75 (1.18, 2.70), and 1.43 (1.00, 2.14) mmol/L] ( P<0.05). The high-density lipoprotein level in the normal group was higher than the high-risk group, medium-risk group, and low-risk group[1.26 (1.05, 1.51) vs 1.16 (0.94, 1.36), 1.15 (0.99, 1.39), and 1.16 (0.97, 1.39) mmol/L, respectively] ( P<0.05). The increases in systolic blood pressure, diastolic blood pressure, body mass index, and body fat content were all moderately negatively correlated with the cerebrovascular function score ( rs=-0.347, -0.335, -0.370, and -0.340, respectively, all P<0.05). The increase in age ( OR=1.012, 95% CI: 1.002-1.022), systolic blood pressure ( OR=1.027, 95% CI: 1.017-1.036), diastolic blood pressure ( OR=1.028, 95% CI: 1.014-1.042), body mass index ( OR=1.157, 95% CI: 1.083-1.237), body fat rate ( OR=1.021, 95% CI: 1.007-1.035), and fasting blood glucose ( OR=1.072, 95% CI: 1.020-1.127) were all positively correlated with the decrease of the cerebrovascular function score; conversely, the increase in skeletal muscle content ( OR=0.967, 95% CI: 0.951-0.982) was negatively correlated with the decrease in cerebrovascular function score (all P<0.05). The area under the curve for the combined prediction of cerebrovascular function integral value by age, systolic blood pressure, diastolic blood pressure, body mass index, body fat rate, skeletal muscle content, and fasting blood glucose was 0.754. Conclusions:As the body mass index and body fat content increase and the skeletal muscle content decreases in the healthy physical examination population, the likelihood of abnormal cerebrovascular function integral values rises; the combination of age, systolic blood pressure, diastolic blood pressure, body mass index, body fat percentage, skeletal muscle content, and fasting blood glucose indicators can predict the increased risk of cerebrovascular function integral values.
2.Correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population
Dianhua DU ; Chunwei WU ; Lan MO ; Xuelin ZHANG ; Wen WU ; Yiping WANG ; Xian WU ; Bo WANG ; Shaohui FENG
Chinese Journal of Health Management 2025;19(4):286-291
Objective:To analyze the correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population.Methods:It was a cross-sectional analysis that employed a simple random sampling method to select 3 496 individuals who underwent healthy physical examinations and cerebrovascular function tests at the Physical Examination Center of the Affiliated Hospital of Guizhou Medical University from January to December 2022. The general information, physical examination data, biochemical examination results, human component analyses, and cerebrovascular function integral data were collected. Based on cerebrovascular function scores, the participants were divided into high-risk group (0-24 points, 70 cases), medium-risk group (25-49 points, 317 cases), low-risk group (50-74 points, 787 cases), and normal group (≥75 points, 2 322 cases). Spearman correlation analysis and receiver operating characteristic (ROC) curve analyses were utilized to assess the correlation and predictive value of obesity measurement indicators and cerebrovascular function integrals.Results:Among the 3 496 subjects included in the analysis, 2 018 were male and 1 478 were female, with an average age of (46.4±7.9) years. The age, systolic blood pressure, diastolic blood pressure, body mass index, waist-to-hip ratio, body fat ratio, body fat content, visceral fat area, fasting blood glucose, total cholesterol, low-density lipoprotein, homocysteine all exhibited an increasing trend as the cerebrovascular function integral value decreased (all P<0.05). The skeletal muscle content in the low-risk group was significantly higher than those in the high-risk group, medium-risk group, and normal group [45.00 (36.80, 50.60) vs 44.10 (36.98, 50.45), 44.50 (37.80, 50.20), and 42.75 (36.30, 48.60) kg, respectively] ( P<0.05). The triglyceride level in the medium-risk group was higher when compared to those in the high-risk group, low-risk group, and normal group[1.87 (1.29, 2.70) vs 1.71 (1.24, 2.80), 1.75 (1.18, 2.70), and 1.43 (1.00, 2.14) mmol/L] ( P<0.05). The high-density lipoprotein level in the normal group was higher than the high-risk group, medium-risk group, and low-risk group[1.26 (1.05, 1.51) vs 1.16 (0.94, 1.36), 1.15 (0.99, 1.39), and 1.16 (0.97, 1.39) mmol/L, respectively] ( P<0.05). The increases in systolic blood pressure, diastolic blood pressure, body mass index, and body fat content were all moderately negatively correlated with the cerebrovascular function score ( rs=-0.347, -0.335, -0.370, and -0.340, respectively, all P<0.05). The increase in age ( OR=1.012, 95% CI: 1.002-1.022), systolic blood pressure ( OR=1.027, 95% CI: 1.017-1.036), diastolic blood pressure ( OR=1.028, 95% CI: 1.014-1.042), body mass index ( OR=1.157, 95% CI: 1.083-1.237), body fat rate ( OR=1.021, 95% CI: 1.007-1.035), and fasting blood glucose ( OR=1.072, 95% CI: 1.020-1.127) were all positively correlated with the decrease of the cerebrovascular function score; conversely, the increase in skeletal muscle content ( OR=0.967, 95% CI: 0.951-0.982) was negatively correlated with the decrease in cerebrovascular function score (all P<0.05). The area under the curve for the combined prediction of cerebrovascular function integral value by age, systolic blood pressure, diastolic blood pressure, body mass index, body fat rate, skeletal muscle content, and fasting blood glucose was 0.754. Conclusions:As the body mass index and body fat content increase and the skeletal muscle content decreases in the healthy physical examination population, the likelihood of abnormal cerebrovascular function integral values rises; the combination of age, systolic blood pressure, diastolic blood pressure, body mass index, body fat percentage, skeletal muscle content, and fasting blood glucose indicators can predict the increased risk of cerebrovascular function integral values.
3.Consideration about Inheritance,Overview of Modernization Development and Development Suggestion of TCM Powder Decoction Pieces
Xuejiao CHENG ; Tao LI ; Xuelin MO ; Chunjie WU
China Pharmacy 2017;28(31):4321-4325
OBJECTIVE:To provide reference for promoting the inherirance and development of TCM powder decoction piec-es. METHODS:By retrieving literature,the inheritance,overview of modernization development,and key points in industrial de-velopment of TCM powder decoction pieces were analyzed,and development suggestion was put forward. RESULTS & CONCLU-SIONS:Aiming at inheritance of TCM powder decoction pieces,suggestions were put forward as explaining scientific connotation of TCM powder decoction pieces,mining the essence of preparation technology,and cultivating comprehensive decoction pieces talents with basic knowledge of powder science. According to the particle size of powder,TCM powder decoction pieces can be di-vided into TCM common powder,TCM ultrafine particle powder,and TCM nano powder. Aiming at the key points of TCM pow-der decoction pieces,such as application scope,particle size and its correlation with the performance of TCM,grinding technology and equipment and quality standards,the developing strategies were put forward as adjusting the suitable application scope,select-ing appropriate particle size,strengthening its performance research,standardizing and innovating the preparation,improving the packaging and sterilization technologies,establishing and implementing the quality standard with characteristics.

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