Spatio-temporal evolution patterns of influenza incidence and its nonlinear spatial correlation with environmental pollutants in China.

BACKGROUND: Currently, the influenza epidemic in China is at a high level and mixed with other respiratory diseases. Current studies focus on regional influenza and the impact of environmental pollutants on time series, and lack of overall studies on the national influenza epidemic and the nonlinear correlation between environmental pollutants and influenza. The unclear spatial and temporal evolution patterns of influenza as well as the unclear correlation effect between environmental pollutants and influenza epidemic have greatly hindered the prevention and treatment of influenza epidemic by relevant departments, resulting in unnecessary economic and human losses. METHOD: This study used Chinese influenza incidence data for 2007-2017 released by the China CDC and air pollutant site monitoring data. Seasonal as well as inter monthly differences in influenza incidence across 31 provinces of China have been clarified through time series. Space-Time Cube model (STC) was used to investigate the spatio-temporal evolution of influenza incidence in 315 Chinese cities during 2007-2017. Then, based on the spatial heterogeneity of influenza incidence in China, Generalized additive model (GAM) was used to identify the correlation effect of environmental pollutants (PM2.5, PM10, CO, SO2, NO2, O3) and influenza incidence. RESULT: The influenza incidence in China had obvious seasonal changes, with frequent outbreaks in winter and spring. The influenza incidence decreased significantly after March, with only sporadic outbreaks occurring in some areas. In the past 11 years, the influenza epidemic had gradually worsened, and the clustering of influenza had gradually expanded, which had become a serious public health problem. The correlation between environmental pollutants and influenza incidence was nonlinear. Generally, PM2.5, CO and NO2 were positively correlated at high concentrations, while PM10 and SO2 were negatively correlated. O3 was not strongly correlated with the influenza incidence. CONCLUSION: The study found that the influenza epidemic in China was in a rapidly rising stage, and several regions had a multi-year outbreak trend and the hot spots continue to expand outward. The association between environmental pollutants and influenza incidence was nonlinear and spatially heterogeneous. Relevant departments should improve the monitoring of influenza epidemic, optimize the allocation of resources, reduce environmental pollution, and strengthen vaccination to effectively prevent the aggravation and spread of influenza epidemic in the high incidence season and areas.

Spatial distribution of anti-mullerian hormone in females of childbearing age in China under the influence of geographical environmental factors.

The Anti-mullerian hormone (AMH) reference value is an important indicator of ovarian function. The main targets of this were to screen the geographical environmental factors that may influence the distribution of AMH reference values in Chinese females of childbearing age, and to further explore the geographical distribution differences of AMH reference values. We gathered the AMH data of 28,402 healthy Chinese females from 62 cities in China for this study in order to conduct a spearman regression analysis to determine the relationship between the AMH and 30 geography factors. The AMH reference value in different regions was forecasted by using a ridge regression model. The magnitude of influence from the geographical factor on different regions was analysed by geographically weighted regression. Ultimately, We were able to figure out the geographic distribution risk prediction of AMH reference values by utilizing the disjunctive Kriging method. The AMH reference value was significantly correlated with the 16 secondary indexes. The geographical distribution of AMH showed a trend of being higher in Qinghai-Tibet and Southern regions, and lower in the Northwest and Northern regions. This study lays the foundation for future investigations into the mechanism of different influencing factors on the reference value of AMH. It is suggested that such regional variations in AMH reference values be taken into account while diagnosing and treating individuals with reproductive medicine.

Effect of geographical factors on reference values of creatine kinase isoenzyme.

The aim of this study was to investigate the geographical spatial distribution of creatine kinase isoenzyme (CK-MB) in order to provide a scientific basis for clinical examination. The reference values of CK-MB of 8697 healthy adults in 137 cities in China were collected by reading a large number of literates. Moran index was used to determine the spatial relationship, and 24 factors were selected, which belonged to terrain, climate, and soil indexes. Correlation analysis was conducted between CK-MB and geographical factors to determine significance, and 9 significance factors were extracted. Based on R language to evaluate the degree of multicollinearity of the model, CK-MB Ridge model, Lasso model, and PCA model were established, through calculating the relative error to choose the best model PCA, testing the normality of the predicted values, and choosing the disjunctive kriging interpolation to make the geographical distribution. The results show that CK-MB reference values of healthy adults were generally correlated with latitude, annual sunshine duration, annual mean relative humidity, annual precipitation amount, and annual range of air temperature and significantly correlated with annual mean air temperature, topsoil gravel content, topsoil cation exchange capacity in clay, and topsoil cation exchange capacity in silt. The geospatial distribution map shows that on the whole, it is higher in the north and lower in the south, and gradually increases from the southeast coastal area to the northwest inland area. If the geographical factors are obtained in a location, the CK-MB model can be used to predict the CK-MB of healthy adults in the region, which provides a reference for us to consider regional differences in clinical diagnosis.

Spatio-temporal distribution of tuberculosis and the effects of environmental factors in China.

BACKGROUND: Although the World Health Organization reports that the incidence of tuberculosis in China is decreasing every year, the burden of tuberculosis in China is still very heavy. Understanding the spatial and temporal distribution pattern of tuberculosis in China and its influencing environmental factors will provide effective reference for the prevention and treatment of tuberculosis. METHODS: Data of TB incidence from 2010 to 2017 were collected. Time series and global spatial autocorrelation were used to analyze the temporal and spatial distribution pattern of tuberculosis incidence in China, Geodetector and Geographically Weighted Regression model were used to analyze the environmental factors affecting the TB incidence. RESULTS: In addition to 2007 and 2008, the TB incidence decreased in general. TB has a strong spatial aggregation. Cities in Northwest China have been showing a trend of high-value aggregation. In recent years, the center of gravity of high-value aggregation area in South China has moved further south. Temperature, humidity, precipitation, PM10, PM2.5, O3, NO2 and SO2 have impacts on TB incidence, and in different regions, the environmental factors show regional differences. CONCLUSIONS: Residents should pay more attention to the risk of developing TB caused by climate change and air pollutant exposure. Increased efforts should be placed on areas with high-value clustering in future public resource configurations.

Associations of environmental factors with total cholesterol level of middle-aged and elderly people in China.

BACKGROUND: Dyslipidemia is a key factor causing cardio cerebrovascular diseases, and the total cholesterol (TC) is an important lipid indicator among them. Studies have shown that environmental factors have a strong association with TC levels. Previous studies only focused on the seasonal variation of TC level and the short-term effects of some environmental factors on TC level over time, and few studies explored the geographical distribution of TC level and quantified the impact of environmental factors in space. METHODS: Based on blood test data which was from China Health and Retirement Longitudinal Study (Charls) database, this study selected the TC level test data of middle-aged and elderly people in China in 2011 and 2015, and collected data from 665 meteorological stations and 1496 air pollutant monitoring stations in China. After pretreatment, the spatial distribution map of TC level was prepared and the regional statistics were made. GeoDetector and geographically weighted regression (GWR) were used to measure the relationship between environmental factors and TC level. RESULTS: The TC level of middle-aged and elderly in China was higher in females than in males, and higher in urban areas than in rural areas, showing a clustered distribution. The high values were mainly in South China, Southwest China and North China. Temperature, humidity, PM10 and PM2.5 were significant environmental factors affecting TC level of middle-aged and elderly people. The impact of pollutants was more severe in northern China, and TC level in southern China was mainly affected by meteorological factors. CONCLUSIONS: There were gender and urban-rural differences in TC levels among the middle-aged and elderly population in China, showing aggregation in geographical distribution. Meteorological factors and air pollutants may be very important control factors, and their influencing mechanism needs further study.

Geographical distribution of reference values of fibrinogen degradation products in healthy adults in China.

To explore the reference values of fibrinogen degradation products (FDP) of healthy adults in different regions of China, determine the relationship between them and geographic factors and determine the geographic distribution of FDP reference value healthy adults in China. The collected FDP reference values of 11,013 healthy adults in 209 Chinese units were firstly determined by spatial autocorrelation to correlate with geographic factors; secondly, using ridge regression analysis and principal component analysis to fit China 2322 FDP reference values of healthy adults in each city, and the selection of the optimal model through comparison; and finally, combined with geostatistical analysis, explore the geographical distribution of FDP reference values of healthy adults in China. The specific distribution of FDP reference values of healthy adults in different regions of China showed a trend of being lower to the north and higher to the south of the Qinling-Huaihe River. If the numerical value of geographical factors in a certain region of China is known, the ridge regression prediction equation can be combined from this: Y = 3.30 - 0.002900X2 - 0.0001400X5 + 0.0001300X6 - 0.009040X6 + 0.0003500X8 - 0.002300X11 + 0.02149X14 - 0.01626X16 ± 0.89 calculates the reference value of FDP for healthy adults in the region and provides a scientific reference for the FDP reference value in different regions of China.

The spatial distribution of the normal reference values of the activated partial thromboplastin time based on ArcGIS and GeoDA.

We explored the variation and spatial distribution of the activated partial thromboplastin time (APTT) reference values of healthy people at different altitudes in China in order to develop a scientific basis for a unified standard. The APTT reference values of 49,020 healthy males (41-75 years old) and 32,447 healthy females (41-75 years old) were collected from 601 work units and 546 work units in China, respectively. The relationship between the APTT reference values and altitude was tested by correlation analysis. Linear regression analysis and curve analysis were employed to predict the APTT reference values in the whole country. Trend surface analysis, the variation function, kriging interpolation, and Getis-Ord Gi* statistic were utilized to reveal the spatial characteristics of the values. The result showed a significant positive correlation between the APTT reference values and altitude. The APTT values for females were prolonged for a greater amount of time than the males in several same areas in China. The spatial contact forms of the APTT reference values of healthy Chinese were mainly "high-high" and "low-low," which was in accord with the first law of geography. The APTT reference values still showed spatial autocorrelation and regional variation. The values were higher in the western and northern areas than in the eastern and southern areas of China. The APTT reference values of people aged 41-75 in China showed regional differences. The APTT reference values in one area can be estimated by using the best prediction model or can be obtained by the geographical distribution.

Associations between geographical environment and systolic pulmonary arterial pressure of Chinese adults: impact analysis and predictive modeling.

Since systolic pulmonary arterial pressure (SPAP) is an important diagnostic indicator for various cardiovascular diseases, it is of great significance to determine scientific SPAP reference value in clinical application. However, the SPAP reference values currently have not been applied under a unified standard, and its formulation does not consider the impacts from geographical environment which has proved to be closely associated with SPAP. This study aims to quantify the impacts of geographical factors on SPAP and formulate scientific SPAP reference values, thereby providing support for more accurate diagnosis. Measured SPAP values of 4550 healthy adults were collected from 88 cities across China, and 11 geographical factors were selected. Four geographical factors with significant impacts on SPAP were determined via correlation analysis, including two positive factors (altitude, soil organic matter) and two negative ones (longitude, annual average temperature). Then partial least-squares regression analysis (PLSR) and trend surface analysis were applied to establish predictive models. Through model test using both collected and simulated SPAP data of control points, the PLSR model was determined to have better prediction accuracy and was selected as optimal model to calculate the SPAP reference values of 2322 cities in China. The predictive results ranged from 22.09 to 31.77 mmHg. Finally, hotspot analysis and kriging interpolation method were applied to explore the spatial distribution of SPAP reference values. The result of spatial analysis shows that SPAP reference values of Chinese adults decreased gradually from the West to East in China. This study indicated the significant impacts of geographical environment on SPAP and established predictive model for determining SPAP reference values, which is expected to help enhance clinical diagnostic accuracy.

Geographical distribution of the P-R interval reference value of Chinese healthy adults.

To explore the relationship between the geographical factors and P-R interval reference value of healthy adults, and to elucidate the geographical distribution of the P-R interval reference value in Chinese adults, to provide the basis for the standard of P-R interval reference value in different regions. The P-R interval reference value of 64,753 healthy adults in 341 cities (counties) level hospitals, research institutes, and universities in China was collected, and 15 geographical data and P-R interval reference value of healthy people were studied, and then 10 geographical factors with correlation were extracted for further analysis. Using spatial autocorrelation analysis to determine the autocorrelation of data space, using backward regression and ridge regression to construct forecast model, and the optimal prediction model is selected by comparing and evaluating the prediction effect of each model, the spatial distribution map of P-R interval reference value of Chinese healthy adults was constructed by statistical analysis. There was a significant correlation between normal reference value of adult P-R interval reference value and geographical factors. The regression model of normal reference value and geographical factors of adult P-R interval reference value was established by ridge regression analysis method: [Formula: see text] =149.2 + 0.02590X2 + 0.0005000X3 + 0.02634X5-0.05890X6 + 0.0008400X7 + 0.01606X8 + 0.2592X9-0.03638X12 + 5.888X13-0.2126X15 ± 8.6, and ArcGIS10.2. In the software interpolation method, the distribution chart of normal reference value of Chinese adult P-R interval reference value was inserted. Knowing the geographical factors of some places in China, we can use this model to estimate the P-R interval reference value in this region, and to obtain the normal P-R interval reference value between adults anywhere in China.

Genistein inhibits nasopharyngeal cancer stem cells through sonic hedgehog signaling.

Genistein, a soy derived isoflavanoid compound, exerts anticancer effects in various cancers. Nasopharyngeal cancer stem cells (NCSCs) are a small subpopulation of cancer cells which are responsible for initiation, progression, metastasis, and recurrence of nasopharyngeal cancer. The present study aimed to investigate the suppressive effects of genistein on NCSCs and its underlying mechanism. NCSCs were enriched from human nasopharyngeal cancer cell lines CNE2 and HONE1 through tumorsphere-forming assay. It was shown that genistein inhibited the tumorsphere formation capacity, decreased the number of EpCAM+ cells, downregulated the expression of NCSCs markers, suppressed cell proliferation, and induced apoptosis of NCSCs. Genistein suppressed the activity of Sonic hedgehog (SHH) signaling, which was important for the maintenance of NCSCs, while activation of SHH signaling by purmorphamine diminished the inhibitory effects of genistein on NCSCs. Our data suggested that genistein inhibited NCSCs through the suppression of SHH signaling. These findings support the use of genistein for targeting NCSCs.

The spatial distribution of BUN reference values of Chinese healthy adults: a cross-section study.

The blood urea nitrogen (BUN) is generally regarded as a significant serum marker in estimating renal function. This study aims to explore the geographical distribution of BUN reference values of Chinese healthy adults, and provide a scientific basis for determining BUN reference values of Chinese healthy adults of different regions according to local conditions. A total of 25,568 BUN reference values of healthy adults from 241 Chinese cities were collected in this study, and 17 geographical indices were selected as explanatory variables. The correlation analysis was used to examine the significance between BUN reference value and geographical factors, then five significant indices were extracted to build two predictive models, including principal component analysis (PCA) and support vector regression (SVR) model, then the optimal model was selected by model test to predict BUN reference values of the whole China, finally the distribution map was produced. The results show that BUN reference value of Chinese healthy adult was characteristically associated with latitude, altitude, annual mean temperature, annual mean relative humidity, and annual precipitation. The model test shows, compared with SVR model, the PCA model possesses superior simulative and predictive ability. The distribution map shows that the BUN reference values of Chinese healthy adult are lower in the east and higher in the west. These results indicate that the BUN reference value is significantly affected by geographical environment, and the BUN reference values of different regions could be seen clearly on distribution map.

The Spatial Distribution Characteristics of the Tumor Biomarker Alpha-fetoprotein: A Cross-section Study.

OBJECTIVES: This study aims to explore the spatial characteristics of the alpha-fetoprotein (AFP) reference value in healthy Chinese adults, and its relationship to geographical location. METHODS: A total of 9396 AFP reference values were collected from patients in 96 administrative units. A correlation analysis and support vector machine (SVM) were employed to extract dependent geographical factors and predict the reference values in the entire country, respectively. A geostatistics analysis was developed to reveal the spatial characteristics of the value. RESULTS: Under the long-term influence of geographical environment, AFP reference values show spatial autocorrelation and regional variation. The values are higher in western and northern areas than in eastern and southern areas of China. CONCLUSIONS: The AFP reference values show regional differences, and this difference should be considered in clinical practice.

[Correlation of Heart Rate and Geographical Environmental Factors with Reference Values of Left Ventricular Ejection Fraction in Healthy Adult Males].

Objective To establish a model for obtaining the reference values of left ventricular ejection fraction(LVEF) in Chinese healthy adult males by exploring the relationships of these reference values with heart rate and geographical environment factors. Methods LVEF and heart rate reference values (X1) were collected from 3502 healthy adult males from 2006 to 2016. Correlation analysis and ridge regression were employed to extract dependent geographical environment factors and predict the LVEF reference values. The Kriging interpolation was applied to reveal the spatial distribution of the LVEF reference values. Results LVEF and heart rate (X1) were significantly correlated with five geographical environment factors. LVEF was negatively correlated with heart rate (X1),latitude (X3),and annual range of temperature (X9) and positively correlated with annual mean air temperature (X6),annual mean relative humidity (X7),and annual precipitation amount (X8). The reference values of LVEF had a negative correlation with heart rate. The ridge regression equation of LVEF reference values and geographical environment factors was as follows:Y=68.464-0.0949X3-0.0619X6-0.00128X7+0.00069X8-0.0199X9±3.329. The equation of LVEF reference values with heart rate and geographical environment factors was Y=75.923-0.1035X1-0.0958X3-0.0741X6+0.00094X7+0.00081X8-0.0211X9±3.288. Conclusion The LVEF reference values among Chinese healthy adult males decreased from south to north. They can be determined based on the regression models after the geographical factors of a certain region are obtained. The new model offers a geographic basis for the establishment of LVEF reference values.

The effect of geographical indices on left ventricular structure in healthy Han Chinese population.

The left ventricular posterior wall thickness (LVPWT) and interventricular septum thickness (IVST) are generally regarded as the functional parts of the left ventricular (LV) structure. This paper aims to examine the effects of geographical indices on healthy Han adults' LV structural indices and to offer a scientific basis for developing a unified standard for the reference values of adults' LV structural indices in China. Fifteen terrain, climate, and soil indices were examined as geographical explanatory variables. Statistical analysis was performed using correlation analysis. Moreover, a back propagation neural network (BPNN) and a support vector regression (SVR) were applied to developing models to predict the values of two indices. After the prediction models were built, distribution maps were produced. The results show that LV structural indices are characteristically associated with latitude, longitude, altitude, average temperature, average wind velocity, topsoil sand fraction, topsoil silt fraction, topsoil organic carbon, and topsoil sodicity. The model test analyses show the BPNN model possesses better simulative and predictive ability in comparison with the SVR model. The distribution maps of the LV structural indices show that, in China, the values are higher in the west and lower in the east. These results demonstrate that the reference values of the adults' LV structural indices will be different affected by different geographical environment. The reference values of LV structural indices in one region can be calculated by setting up a BPNN, which showed better applicability in this study. The distribution of the reference values of the LV structural indices can be seen clearly on the geographical distribution map.

The acquisition of goal-directed actions generates opposing plasticity in direct and indirect pathways in dorsomedial striatum.

A cortical-basal ganglia network involving, particularly, the posterior region of dorsomedial striatum (DMS) has been implicated in the acquisition of goal-directed actions; however, no direct evidence of learning-related plasticity in this striatal region has been reported, nor is it known whether, or which, specific cell types are involved in this learning process. The striatum is primarily composed of two classes of spiny projection neurons (SPNs): the striatonigral and striatopallidal SPNs, which express dopamine D1 and D2 receptors, respectively. Here we establish that, in mice, the acquisition of goal-directed actions induced plasticity in both D1- and D2-SPNs specifically in the DMS and, importantly, that these changes were in opposing directions; after learning, AMPA/NMDA ratios were increased in D1-SPNs and reduced in the D2-SPNs in the DMS. Such opposing plasticity could provide the basis for rapidly rebiasing the control of task-specific actions, and its dysregulation could underlie disorders associated with striatal function.

Formononetin inhibits enterovirus 71 replication by regulating COX- 2/PGE2 expression.

BACKGROUND: The activation of ERK, p38 and JNK signal cascade in host cells has been demonstrated to up-regulate of enterovirus 71 (EV71)-induced cyclooxygenase-2 (COX-2)/ prostaglandins E2 (PGE2) expression which is essential for viral replication. So, we want to know whether a compound can inhibit EV71 infection by suppressing COX-2/PGE2 expression. METHODS: The antiviral effect of formononetin was determined by cytopathic effect (CPE) assay and the time course assays. The influence of formononetin for EV71 replication was determined by immunofluorescence assay, western blotting assay and qRT-PCR assay. The mechanism of the antiviral activity of formononetin was determined by western blotting assay and ELISA assay. RESULTS: Formononetin could reduce EV71 RNA and protein synthesis in a dose-dependent manner. The time course assays showed that formononetin displayed significant antiviral activity both before (24 or 12 h) and after (0-6 h) EV71 inoculation in SK-N-SH cells. Formononetin was also able to prevent EV71-induced cytopathic effect (CPE) and suppress the activation of ERK, p38 and JNK signal pathways. Furthermore, formononetin could suppress the EV71-induced COX-2/PGE2 expression. Also, formononetin exhibited similar antiviral activities against other members of Picornaviridae including coxsackievirus B2 (CVB2), coxsackievirus B3 (CVB3) and coxsackievirus B6 (CVB6). CONCLUSIONS: Formononetin could inhibit EV71-induced COX-2 expression and PGE2 production via MAPKs pathway including ERK, p38 and JNK. Formononetin exhibited antiviral activities against some members of Picornaviridae. These findings suggest that formononetin could be a potential lead or supplement for the development of new anti-EV71 agents in the future.

The relationship between left ventricle myocardial performance index of healthy women and geographical factors.

The study focused on the relationship between geographical factors and left ventricular myocardial performance index (MPI)reference value, analyed the different distribution of MPI, and then provided a scientific basis for clinical examination. This study collected MPI reference values of 2545 healthy women from 91 cities in China, used the Moran's index to determin the spatial relationship, selected 25 geographical factors, examined the significance between MPI and geographical factors by correlation analysis, through the significance test, and extracted seven significant factors to build the artificial neural network (ANN) model and principal component analysis (PCA) model. Through calculating the relative error, the ANN model was chosen as the better model to predict the values. By normality test for the predicted values, the geographical distribution was made by disjunctive kriging interpolation. The predicted values decrease from north to south. If geographical factors are obtained in one location, the MPI of healthy women in this area can be predicted by the ANN model. Synthesizing the influence of physiological and geographical could be more scientific to formulate the MPI reference value.

Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors.

The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X1), annual duration of sunshine (X2), annual mean air temperature (X3), annual mean relative humidity (X4), annual precipitation amount (X5), annual air temperature range (X6) and annual mean wind speed (X7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging's method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

[Geographical distribution of left ventricular Tei index based on principal component analysis].

OBJECTIVE: To provide a scientific standard of left ventricular Tei index for healthy people from various region of China, and to lay a reliable foundation for the evaluation of left ventricular diastolic and systolic function. METHODS: The correlation and principal component analysis were used to explore the left ventricular Tei index, which based on the data of 3 562 samples from 50 regions of China by means of literature retrieval. Th e nine geographical factors were longitude(X1), latitude(X2), altitude(X3), annual sunshine hours (X4), the annual average temperature (X5), annual average relative humidity (X6), annual precipitation (X7), annual temperature range (X8) and annual average wind speed (X9). ArcGIS soft ware was applied to calculate the spatial distribution regularities of left ventricular Tei index. RESULTS: There is a significant correlation between the healthy people's left ventricular Tei index and geographical factors, and the correlation coefficients were -0.107 (r1), -0.301 (r2), -0.029 (r3), -0.277 (r4), -0.256(r5), -0.289(r6), -0.320(r7), -0.310 (r8) and -0.117 (r9), respectively. A linear equation between the Tei index and the geographical factor was obtained by regression analysis based on the three extracting principal components. The geographical distribution tendency chart for healthy people's left Tei index was fitted out by the ArcGIS spatial interpolation analysis. CONCLUSION: The geographical distribution for left ventricular Tei index in China follows certain pattern. The reference value in North is higher than that in South, while the value in East is higher than that in West.

Influence of geographical environment on retinol-binding protein reference values in Chinese men.

This study combined geographic factors to predict Chinese healthy male RBP reference values from a geographic perspective, with the aim of exploring the spatial distribution and regional differences in Chinese healthy male Retinol-Binding Protein(RBP) reference values, and then providing a theoretical basis for medical diagnosis of healthy male RBP reference values in different regions of China. Using the actual measured RBP values of 24,502 healthy men in 256 cities in China combined with 16 geographical factors as the base data, the spatial autocorrelation, correlation analysis and support vector machine were used to predict the RBP reference values of healthy men in 2322 cities in China, and to generate a spatial distribution map of the RBP reference values of healthy men in China. It was found that the spatial distribution of healthy male RBP reference values in China showed a trend of gradual increase from the first to the third terrain steps. Combined with the distribution map, it is suggested that the RBP reference values of healthy men in China should be divided into the low value zone of the first-level terrain step (25mg/L~40mg/L), the middle value zone of the second-level terrain step (40mg/L~45mg/L) and the high value zone of the third-level terrain step (45mg/L~52mg/L).