NAFLD Detection Rate And Establishment Risk Model In Non-Obese Physical Examination Population In Functional Communities

PurposeTo grasp the prevalence of NAFLD among non-obese people in functional communities in Hohhot,and provide effective clinical guidance and basis for early prevention of the occurrence and development of NAFLD in the future.The risk prediction model of NAFLD in non-obese people is established through historical cohort,which provides convenient,fast and effective new ideas and methods for early identification of non-obese high-risk groups.method1.Through the collection of general data,laboratory data,and ultrasound examination data of 4 functional communities that underwent annual physical examinations at the Physical Examination Center of the Affiliated Hospital of Inner Mongolia Medical University from January 2018 to December 2018,the final A cross-sectional study of 3927 people was selected to understand the prevalence of NAFLD among non-obese physical examination populations under different stratifications.2.According to the inclusion and exclusion criteria,a historical cohort study was conducted on 1,534 functional community populations who were selected for annual physical examination at the Physical Examination Center of the Affiliated Hospital of Inner Mongolia Medical University from January 2018 to December 2021.R4.0.5 software was used to generate random numbers by 7:3 ratio,1534 subjects were randomly divided into modeling group(1073 people)and validation group(461 people).The nomogram(risk model)was constructed based on the Cox univariate and multivariate analysis results.Before drawing the nomogram,AUC(area under the ROC curve)and Hosmer-Lemeshow test were used to evaluate the established prediction model to judge whether the model has good discriminative ability and calibration ability.result1.Detection rate of NAFLD in non-obese physical examination population in functional communityThe detection rate of non-obese NAFLD population in functional communities in Hohhot was 26.17%.Men have a higher detection rate than women,and with the increase of age,the detection rate of NAFLD gradually increases,although the detection rate is the lowest in the18-30 age group,which can still be as high as 17.04%.In different functional communities,the detection rate of commercial service industry personnel was 32.55%;the detection rate of civil servants was 31.63%;the detection rate of enterprise personnel was 28%;the detection rate of public institution personnel was 17.89%.Under different BMI stratification,the detection rate of NAFLD showed an increasing trend with the increase of BMI.In addition,the detection rate of NAFLD in both smoking and drinking population was higher than that in non-smoking and non-drinking population(P<0.05).Among the single metabolic abnormality components,the detection rates of NAFLD in people with abnormal blood pressure,dyslipidemia and impaired fasting glucose were 39.72%,55.61%and 51.96%,respectively;while the detection rates of NAFLD in people with normal blood pressure,normal blood lipids and normal fasting glucose were The output rates were23.07%,12.63%,and 24.52%,respectively.Under different metabolic components,the detection rate of NAFLD was higher in the population with any metabolic abnormality than in the population without the abnormal component(P<0.05).Under the multiple metabolic abnormal components,the detection rate of people with abnormal blood pressure and impaired fasting glucose was 56.63%;the detection rate of NAFLD in people with abnormal blood pressure and dyslipidemia was 48.08%;the detection rate of NAFLD in people with dyslipidemia and impaired fasting glucose The detection rate was 60.48%;the detection rate of NAFLD was 66.67%in the population with abnormal three metabolic components(P<0.05).2.Establishment of NAFLD risk model in functional community non-obese physical examination population2.1 A total of 1534 subjects were included in this study,including 1073 in the modeling group and 461 in the validation group.A total of 282 people developed NAFLD in all study subjects,with a cumulative incidence rate of 18.4%and an annual incidence rate of approximately 6.47%.The mean follow-up time was 32.35 months.Among them,the number of patients with NAFLD in the modeling group was 197,with a cumulative incidence rate of18.36%;the number of patients with NAFLD in the validation group was 85,with a cumulative incidence rate of 18.44%.2.2 Univariate Cox regression analysis showed that gender,BMI,SBP,DBP,RBC,Hb,HCT,MCHC,PLR,ALT,AST/ALT,GGT,ALP,Scr,BUN,SUA,TG,TC,FPG,HDL-C,Both LDL-C were associated with the occurrence of NAFLD(all P<0.1).2.3 Multivariate Cox regression analysis showed that gender(HR=0.450),HDL-C(HR=0.613)were protective factors for new NAFLD,BMI(HR=2.671),Hb(HR=1.512),ALT(HR=1.219),AST/ALT(HR=1.423),ALP(HR=1.211),TG(HR=1.185)were new risk factors for NAFLD(all P<0.05).2.4 Based on the results of multivariate Cox regression analysis,nomogram(risk model)was drawn using R statistical software.In the Hosmer-Lemeshow goodness of fit test,the modeling group:X~2=8.231,P=0.411;the validation group:X~2=6.889,P=0.549(all P values>0.05),indicating that the model has a good goodness of fit.The calibration curve results of the modeling group and the validation group show that the predicted results of the model are close to the actual occurrence rate,indicating that the model has good calibration ability.According to the area under the ROC curve,the C index of the modeling group was0.747(0.710-0.785),and the C index of the verification group was 0.765(0.707-0.822),indicating that the model has good discriminative ability.conclusion1.For non-obese people in functional communities in Hohhot,in the future clinical practice,we should focus on the factors of male,increasing age,and increasing BMI,so as to help clinicians carry out more targeted prevention and intervention work in the future.In terms of NAFLD intervention,quitting smoking and drinking may have a certain significance in preventing the occurrence of NAFLD,and taking relevant countermeasures for each component of the metabolic syndrome can better reduce the adverse effects in the future.In different functional communities,large-scale lectures such as health lecture halls and on-site free clinic activities are regularly organized,and measures such as inter-work exercises,tobacco control and healthy diet education are carried out according to the health characteristics of the party and government units,and supervision and control are strengthened,which can help functional Community population can better achieve health promotion role.2.Based on eight risk factors including gender,BMI,Hb,ALT,AST/ALT,ALP,TG,and HDL-C,this study established a NAFLD risk nomogram model for non-obese people in functional communities to predict the risk in the next 3 years.It is helpful to identify high-risk groups,improve people’s awareness of disease risk,and help clinicians to carry out clinical assessment and formulate primary prevention strategies as soon as possible.