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To construct the Bayesian network model of H-type hypertension in middle-aged and elderly people, and to explore the influencing factors of H-type hypertension and the network relationship between factors, and the strength of each influencing factor on H-type hypertension.
A total of 1 119 middle-aged and elderly people who underwent physical examination in the hospital health management center from May 2022 to April 2023 were selected as the research objects and relevant data were collected. Univariate logistic regression analysis and multivariate logistic regression analysis models were used for preliminary screening of variables, “bnlearn” Bayesian network software package was used for model construction, and Netica software was used for model inference.
Logistic regression analysis model was used to screen the variables, such as age, gender, education level, smoking, drinking, body mass index(BMI), fasting blood glucose, etc. FBG, total cholesterol(TC), triglyceride(TG), high density lipoprotein cholesterol((HDL-C), low density lipoprotein cholesterol(LDL-C) and uric acid(UA) were included in the Bayesian network model. A Bayesian network model of H-type hypertension related factors in middle-aged and elderly people with 13 nodes and 16 directed edges was constructed by using 12 selected variables as network nodes. Age, FBG, TG, HDL-C and BMI were directly related to H-type hypertension, while gender, smoking, drinking, educational level, TC, LDL-C and UA were indirectly related to H-type hypertension. When the age was≥60years old, FBG≥6.85 mmol/L, BMI≥24.83 kg/m2, HDL-C≥1.02 mmol/L, TG<1.6 mmol/L, the risk of H-type hypertension reached 0.565.
The Bayesian network model reveals the direct and indirect factors and correlation strength of H-type hypertension in middle-aged and elderly people, clarifies the complex network relationship between factors, and provides a scientific basis for early prevention of H-type hypertension in middle-aged and elderly people.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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