Analysis of influencing factors of dental fluorosis in children based on logistic regression and classification tree model / 中华地方病学杂志

Objective:To analyze the influencing factors of dental fluorosis of children in the drinking-water-borne endemic fluorosis (referred to as drinking-water-borne fluorosis) areas with qualified drinking water.Methods:In 2020 and 2021, the cluster sampling method was used to select the children aged 8 to 12 years old from the drinking-water-borne fluorisis areas with qualified drinking water in Tianjin City for water and urine fluoride detection, dental fluorosis examination and questionnaire survey, and logistic regression and classification tree model were used to analyze the influencing factors of dental fluorosis in children.Results:A total of 3 795 cases children aged 8 to 12 years old were investigated, and 1 001 cases of dental fluorosis were detected, and the detection rate of dental fluorosis was 26.38% (1 001/3 795). The results of logistic analysis showed that age [odds ratio ( OR) = 1.193, 95% confidence interval ( CI): 1.115 - 1.277], high urinary fluoride (1.84 - 19.40 mg/L, OR = 1.510, 95% CI: 1.169 - 1.952) and the number of permanent residents at home ≥6 ( OR = 1.377, 95% CI: 1.090 - 1.739) were risk factors of dental fluorosis in children; and the mother's with higher education level (college degree or above, OR = 0.664, 95% CI: 0.441 - 0.999), the years of water improvement ≥5 years (5 - < 10 years, OR = 0.193, 95% CI: 0.157 - 0.238; ≥10 years, OR = 0.254, 95% CI: 0.193 - 0.333) were protective factors of dental fluorosis in children. The results of classification tree model analysis showed that the years of water improvement contributed the most to the prevalence of dental fluorosis among children in the drinking-water-borne fluorisis areas with qualified drinking water, followed by age, number of permanent residents at home and urinary fluoride. The area under the receiver operating characteristic curve (AUC) of logistic regression model and classification tree model were 0.730 (95% CI: 0.711 - 0.748) and 0.721 (95% CI: 0.702 - 0.739), respectively, with good fitting effect. Conclusion:The detection rate of children's dental fluorosis in the drinking-water-borne fluorosis areas with qualified drinking water is mainly related to the years of water improvement, age, the number of permanent residents at home and urinary fluoride.

Relationship between dietary patterns and sleep disorders among health screening population in Changsha / 中南大学学报(医学版)

OBJECTIVES@#Sleep disorders directly affect health-related quality of life, so it is of great significance to investigate the risk factors of sleep disorders and to actively intervene. This study aims to investigate the relationship between dietary patterns and associated factors and sleep disorders among the health screening populations in Changsha.@*METHODS@#A cross-sectional study was carried out in 86 073 subjects aged 18-70 years old who underwent the health screening. The association between dietary patterns and sleep disorders was analyzed. The associated factors for sleep disorders were identified via by principal component analysis and classification tree model.@*RESULTS@#The overall prevalence of reporting sleep disorders was 18.64%. Four major dietary patterns (healthy, snacks, whole-grain, and fried food patterns) were identified. In logistic regression, snacks and fried food patterns had higher risk of sleep disorders. The whole-grain pattern was a protective factor for sleep disorders. Nine associated factors including age, susceptibility to anxiety, snacking parterns, feelings of depression, chronic pain, physical activity, educational level, gender, and weight, and 9 groups at high risk for sleep disorders were identified by classification tree model.@*CONCLUSIONS@#Sleep disorders are prevalent in the health screening population of Changsha. There is a close association between snacks dietary patterns and sleep disorders. It is necessary to promote healthy and reasonable diet, and keep good lifestyle for the prevention and control of sleep disorders. Health management after physical examination should take different health interventions for high-risk groups with different characteristics of sleep disorders.

Analysis of HIV infection status and the related factors among male students who have sex with men from voluntary counseling and testing clinics by classification tree model in Changzhou City, Jiangsu Province / 中华预防医学杂志

Objective@#To analysis the status of HIV infection and the related factors among students of men who have sex with men (MSM) from voluntary counseling and testing (VCT) clinics in Changzhoucity Jiangsu province.@*Methods@#A total of 236 subjects with previous male sexual history, 16-25 years of age and less than 3 months of confirmation time of HIV positive infection were recruited in Changzhou from January 2014 to December 2017. Questionnaires were conducted and plasma samples were collected for selenium and HIV antibody testing. The relevant factors of HIV infection among MSM were screened by classification tree model. The model was evaluated using cross validation and receiver operating characteristic (ROC) curve.@*Results@#The age of subjects was (20.76±1.97) years old. The age of the first sex with men was (19.14±1.85) years old and the plasma selenium content was (82.59±11.99) ng/ml. Of the 236 subjects, 74.58% (176 cases) were college students or undergraduates; 8.90% (21 cases) were diagnosed with venereal diseases in the last year; 80.93% (191 cases) received health services in the last year, and the positive rate of HIV antibody was 25.00% (59 cases). Four relevant factors were screened by the classification tree model, including the diagnosis of sexual transmitted diseases (STDs) in the last year, health services in the last year, plasma selenium level and education level. The most important factor was whether STDs were diagnosed in the last year. The estimate of re-substitution and cross-validation of the classification tree model was 0.186 and 0.195, and the standard error was 0.025 and 0.026, respectively. The area under the ROC was 0.706 (P<0.001).@*Conclusion@#The MSM HIV antibody positive rate of VCT students in Changzhou City, Jiangsu Province was 25.0%. The diagnosis of STDs in the last year, receiving health services in the last year, plasma selenium level and education level were relevant factors of HIV infection.

Classification Tree Model Analysis on Risk Factors of Diabetic Kidney Disease to Progress to ESRD for CKD3-4 Stages Patients / 中山大学学报(医学科学版)

@#【Objective】To analyze the risk factors of progression to end-stage renal disease（ESRD）in patients with diabetic kidney disease（DKD），and screen the high-risk population for early prevention.【Methods】The clinical data of 231 patients with diabetic nephropathy in our hospital were collected and followed up for 3 years. According to whether ESRD occurred，they were divided into non-progressing ESRD group（133 cases）and ESRD group（98 cases）. Classification tree model was used to analyze the risk factors related to ESRD，and the high-risk population was screened by node gain analysis.【Results】Four important explanatory variables were screened out by the classification tree model from the candi⁃ date variables related to early renal damage，including apolipoprotein B（ApoB），gender，diabetic retinopathy，systemic blood pressure（SBP）. ApoB level was an important factor for DKD progression. For DKD patients with the chronic kidney disease （CKD）3~4 stageswith ApoB> 1.14 mmol/L，theprobabilityofprogression toESRDfor 3 yearswas 75.0 %，and ifat the same time with diabetic retinopathy，the probability was 79.7 %.【Conclusion】The classification tree model can analyze the risk factors of progression to ESRD in DKD patients effectively，to identify the characteristics of high-risk populations.

Classification tree model analysis on related factors of different stages of kidney in type 1 diabetic patients / 中华肾脏病杂志

Objective To analyze the related factors of micro-albuminuria and macroalbuminuria in type 1 diabetes mellitus (DM) in the classification tree model,and to screen the high risk population of diabetic kidney disease.Methods 394 patients with type 1 diabetes were enrolled in the hospital from 2008 to 2015.According to glomerular filtration rates and urine albumin quantification,the patients were divided into type 1 diabetes group (299 cases),micro-albuminuria group (73 cases) and macro-albuminuria group (22 cases).The classification tree model was utilized to analyze related factors of the different stages of proteinuria,and the high-risk population was screened by node gain analysis.Results Four important explanatory variables were screened out by the classification tree model from the 27 candidate variables related to primary renal damage,including retinopathy,fibrinogen,waist-hip ratio (WHR),red blood cell distribution width (RDW).Retinopathy was an major factor of DKD.The probability of macro-albuminuria in retinopathy and WHR ＞ 0.82 group was 43.8％,and if at the same time RDW ＞ 0.14,the probability of macro-albuminuria was 88.9％.Conclusions The classification tree model can analyze factors of the separate stages of proteinuria in type 1 diabetic patients effectively.Retinopathy is the major influential factors of type 1 diabetic patients with proteinuria.

Classification tree model analysis on related factors of different stages of kidney in type 1 diabetic patients / 中华肾脏病杂志

Objective To analyze the related factors of micro-albuminuria and macroalbuminuria in type 1 diabetes mellitus (DM) in the classification tree model,and to screen the high risk population of diabetic kidney disease.Methods 394 patients with type 1 diabetes were enrolled in the hospital from 2008 to 2015.According to glomerular filtration rates and urine albumin quantification,the patients were divided into type 1 diabetes group (299 cases),micro-albuminuria group (73 cases) and macro-albuminuria group (22 cases).The classification tree model was utilized to analyze related factors of the different stages of proteinuria,and the high-risk population was screened by node gain analysis.Results Four important explanatory variables were screened out by the classification tree model from the 27 candidate variables related to primary renal damage,including retinopathy,fibrinogen,waist-hip ratio (WHR),red blood cell distribution width (RDW).Retinopathy was an major factor of DKD.The probability of macro-albuminuria in retinopathy and WHR ＞ 0.82 group was 43.8％,and if at the same time RDW ＞ 0.14,the probability of macro-albuminuria was 88.9％.Conclusions The classification tree model can analyze factors of the separate stages of proteinuria in type 1 diabetic patients effectively.Retinopathy is the major influential factors of type 1 diabetic patients with proteinuria.

Classification tree model analysis of influencing factors for hepatocyte steatosis in patients with chronic hepatitis B / 临床肝胆病杂志

ObjectiveTo investigate the influencing factors for hepatocyte steatosis in patients with chronic hepatitis B (CHB) and the high-risk population by classification tree model analysis, and to establish a simple method to assess the risk of hepatocyte steatosis in CHB patients. MethodsThe clinical data and pathological results of the CHB patients who underwent liver biopsy in Department of Infectious Diseases, The First People's Hospital of Shunde, from January 2006 and December 2014 were collected. The classification tree model was applied to analyze the influencing factors for hepatocyte steatosis, and index value curve, misclassification matrix, and error of estimation were applied for overall evaluation of classification results of the classification tree model. ResultsThe influencing factors for hepatocyte steatosis in CHB patients were body mass index (BMI), total cholesterol, and low-density lipoprotein, and the most important factor was BMI. This classification tree model had a sensitivity of 84.3%, a specificity of 81.5%, an accuracy of 82.9%, and an error of estimation of 0.171, suggesting that this model was well fitted. ConclusionClassification tree model analysis shows that the pathogenesis of hepatocyte steatosis in CHB patients is closely related to the influencing factors BMI, total cholesterol, and low-density lipoprotein. A simple classification method is established based on these factors to evaluate the risk of hepatocyte steatosis in CHB patients. It is necessary to conduct further clinical studies to investigate the clinical value of this method.

Classification tree model analysis on related factors of early renal damage in type 2 diabetic patients / 中华肾脏病杂志

Objective To analyze the impact factors for early renal damage in type 2 diabetic patients by the classification tree model.Methods A total of 601 patients with type 2 diabetes were enrolled.According to glomerular filtration rates and urine albumin quantification,the patients were divided into type 2 diabetes group (418 cases) and early diabetic renal damage group (183 cases).The clinical data of the patients were recorded to analyze the main influential factors for the microalbuminuria of type 2 diabetic patients using the Exhaustive CHAID classification tree algorithm.Results Six important explanatory variables were screened out by the classification tree model from the 34 candidate variables related to early renal damage,including fibrinogen,history of hypertension,retinopathy,Cys C levels,SBP and peripheral neuropathy.Elevated fibrinogen was the main factor.Conclusion The classification tree model can analyze the major influential factors of early renal damage in type 2 diabetic patients effectively,and it can help develop the prevention and treatment methods.