Analysis On The Risk Of NAFLD In Health Examination People In Binhai County

Objective: To study the general situation of the resident population and the prevalence of fatty liver in the Binhai County People ’s Hospital for three consecutive years at the Binhai County People ’s Hospital to participate in a free health checkup supported by the public,and to determine the risk of fatty liver occurrence and development.Factors to provide theoretical basis and useful guidance for the development of intervention programs for chronic diseases related to lifestyles such as fatty liver,hyperglycemia,and hyperlipidemia in the region.This will maximize the effectiveness of free health checkups for the entire population,reduce the incidence of chronic diseases in the region,improve the capacity and management level of chronic diseases in the region,and contribute to the implementation of the Healthy China 2030 Plan.Methods: In this study,1652 permanent residents of Binhai County who participated in a free health checkup at the Binhai County People’s Hospital for three consecutive years were selected,and their three-year abdominal color Doppler ultrasound,biochemical indicators,and general conditions were obtained from the universal health checkup system.The physical examination information and other data are sorted and analyzed,and the data is processed and analyzed using statistical methods.The main statistical methods arec2 test,trendc2 test,completely random design t test,repeated measures analysis of variance,Analysis of Generalized Estimation Equations,univariate logistic regression analysis,and multivariate logistic regression analysis.Result: The results show that the incidence of fatty liver in the three years of 2017,2018,and 2019 were 35.96%,39.71%,and 34.56%,of which the prevalence of fatty liver was the highest in 2018,and the difference was statistically significant compared with the previous year.Significance(compared to 2018 withc2= 4.95,P<0.05;2019 compared with 2018,c2= 9.37,P<0.05).1.Differences in the prevalence of fatty liver between age and sex The trend of fatty liver by agec2 test found that there was a linear correlation between fatty liver and age(= 31.19,P<0.01),with the highest prevalence between 50 and 69 years of age.When comparing by sex,the data in 2018 and 2019 showed that the prevalence of fatty liver in men was higher than that in women(= 9.50,P<0.01).2.Differences in the prevalence of fatty liver based on various indicators(1)When comparing blood pressure points,the prevalence of fatty liver was higher in people with abnormal blood pressure than in people with normal blood pressure(= 41.73,P<0.01).(2)When comparing liver function,the prevalence of fatty liver was higher in people with abnormal liver function than in people with normal liver function = 41.02,(P<0.01);(3)The prevalence of fatty liver in people with dyslipidemia is higher than that in people with normal lipids when comparing blood lipids(= 135.92,P<0.01);(4)When comparing blood glucose,the prevalence of fatty liver was higher in people with abnormal blood glucose than in people with normal blood glucose(=114.34,P<0.01);(5)When comparing renal function,there is no statistical difference in the prevalence of fatty liver between normal renal function abnormalities and normal people.(= 0.54,P = 0.85);(6)When comparing the body mass index,the trend c2 test showed that There is a linear correlation between the prevalence of fatty liver and body mass index.The larger the body mass index,the higher the prevalence of fatty liver(= 294.26,P<0.01).3.Analysis of three-year related indicators of fatty liver population and sub-fatty liver population When analyzing the three-year biochemical indicators of fatty liver and non-fatty liver people,it was found that at the level of α = 0.01,in addition to the three indicators of total bilirubin,creatinine and urea,the body mass index,alanine aminotransferase,The differences among aspartate aminotransferase,total cholesterol,blood glucose,triglycerides,etc.were statistically significant.However,for the three indicators of total bilirubin,creatinine and urea,the analysis results of each year are not exactly the same.In the 2017 study,there was no statistically significant difference between these three indicators in the fatty liver and non-fatty liver populations(P> 0.05).In the 2018 study,the difference in total bilirubin between the fatty liver population and the non-fatty liver population was statistically significant at the level of α = 0.05(P = 0.035),but the difference between creatinine and urea was not statistically significant.(P> 0.05);In the 2019 study,the difference in creatinine between the fatty liver population and the non-fatty liver population was statistically significant at the level of α = 0.05(P = 0.013),while the total bilirubin and urea The difference was not statistically significant(P> 0.05).4.Analysis of repeated measurement data of some indicators of the study population for three years Repeated measurement analysis of variance for the three-year physical examination data of the study population found that the differences in the other indicators at the three-year time point were statistically significant except for the body mass index and triglycerides.Analysis of the generalized estimation equations for these indicators found that blood pressure,body mass index,alanine aminotransferase,aspartate aminotransferase,total cholesterol,triglycerides,blood glucose,triglycerides and other indicators entered the generalized estimation equation.5.Univariate and multivariate logistic regression analysis Perform a single factor logistic regression analysis on gender,age,blood pressure,body mass index,alanine aminotransferase,aspartate aminotransferase,total cholesterol,triglycerides,blood glucose,total bilirubin,creatinine,urea and other indicators in the participating population The multi-factor logistic regression analysis of scientifically meaningful indicators showed that the five indicators of blood pressure,body mass index,alanine aminotransferase,blood glucose,and triglycerides were independent risk factors for fatty liver.In 2018,age is also an independent risk factor for fatty liver.In 2017 and 2019,total cholesterol was an independent risk factor for fatty liver.Further interaction analysis showed that the interaction between factors such as body mass index,alanine aminotransferase,blood glucose,total cholesterol,triglycerides,and hypertension can increase the risk of fatty liver disease.Conclusion: 1.The study found that the prevalence of fatty liver in the three years from 2017 to 2019 in Binhai County ranged from 34.56% to 39.71%,and the prevalence was linearly related to age,with increasing age,Generally showing an "inverted U" shape.The prevalence of fatty liver in people aged 50-69 years is higher than in other age groups.After grouping by sex,the prevalence of fatty liver in men is higher than that in women.2.The body mass index,alanine aminotransferase,aspartate aminotransferase,total cholesterol,triglyceride,blood glucose and other indicators of fatty liver population and non-fatty liver population are significantly different.These indicators can be used for the auxiliary diagnosis and intervention effect of fatty liver evaluation of.3.The Generalized Estimation Equation:Logit(E)=10.535+0.238×HBP-0.318×BMI-0.04×ALT+0.047×AST-0.168×TC-0.121×GLU-0.345×TG The probability of an individual suffering from fatty liver : P=1/(1 +(1/Exp(Logit(E)))=1/(1+(1/Exp(10.535+0.238×HBP-0.318×BMI-0.04×ALT+0.047×AST-0.168×TC-0.121×GLU-0.345×TG)))4.Univariate and multivariate logistic regression analysis showed that blood pressure,body mass index,alanine aminotransferase,total cholesterol,blood glucose,triglycerides and other factors are independent risk factors for fatty liver,and the interaction between them can increase the incidence of fatty liver risk.5.In the future health education and health management work,it is necessary to increase publicity of health knowledge,promote healthy lifestyles,increase health education and health intervention,gradually reduce the incidence of fatty liver in local residents,and improve other areas in the region.Incidence of metabolic diseases.