Correlation and predictive value of obesity measurement indicators and cerebrovascular function scores in healthy physical examination population
10.3760/cma.j.cn115624-20240606-00471
- VernacularTitle:健康体检人群肥胖测量指标与脑血管功能积分值的相关性及预测价值
- Author:
Dianhua DU
1
;
Chunwei WU
;
Lan MO
;
Xuelin ZHANG
;
Wen WU
;
Yiping WANG
;
Xian WU
;
Bo WANG
;
Shaohui FENG
Author Information
1. 贵州医科大学附属医院体检中心，贵阳 550004
- Publication Type:Journal Article
- Keywords:
Obesity;
Cerebrovascular function score;
Risk factors;
Predictive capability
- From:
Chinese Journal of Health Management
2025;19(4):286-291
- CountryChina
- Language:Chinese
-
Abstract:
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.
