ABSTRACT
@#Abstract: Objective （ Based on the data from the ″Occupational Diseases Hazardous Items Reporting System″ hereinafter ）， referred to as the ″Reporting System″ a method was constructed to estimate the number of occupational dust exposed workers （ ） in coal mining and washing enterprises hereinafter referred to as "coal workers" at the provincial administrative level. Methods ， A typical sampling method was used to study 1 808 coal enterprises in Shanxi Province Inner Mongolia Autonomous ， ， Region Shaanxi Province and Xinjiang Uygur Autonomous Region in 2020 in the Reporting System. Based on the data of 1 217 ， ， - coal enterprises that were coal mining or integrated coal mining and washing enterprises a multi level model was established to analyze the association between the number of coal workers and raw coal production. Two scenarios were set up based on the ， enterprise scale composition ratio to estimate the number of underreported coal workers and the number of coal workers in each Results provincial administrative region was corrected. The data of the Reporting System in 2020 showed that the ranking of ， raw coal production and the number of coal workers from most to least were Shanxi Province Inner Mongolia Autonomous ， ， Region Shaanxi Province and Xinjiang Uygur Autonomous Region with a total of 1 002 842 coal workers. The random intercept ， model using raw coal production enterprise scale and their interaction terms was fitted optimally with a −2 log likelihood value of 2 005.96 and Akaike information criterion value of 2 017.95. The factors affecting the number of coal workers included raw ， coal production and its interaction with the scale of enterprises. For every 1.00% change in raw coal production the number of ， coal workers in small and micro enterprises changed by 0.62% and the number of coal workers in large and medium enterprises changed by 0.13% more than that in small and micro enterprises. The corrected total number of coal workers for the four ， Conclusion provincial administrative regions was 1 125 515 and 1 089 321 for the two hypothetical scenarios respectively.The multi level model constructed with the data of raw coal production enterprise scale and their interaction terms of four ， provincial administrative regions could estimate the number of coal workers accurately and could better correct the number of coal workers in each provincial administrative region.
ABSTRACT
Objective@#For computer-aided Chinese medical diagnosis and aiming at the problem of insufficient segmentation, a novel multi-level method based on the multi-scale fusion residual neural network (MF2ResU-Net) model is proposed.@*Methods@#To obtain refined features of retinal blood vessels, three cascade connected U-Net networks are employed. To deal with the problem of difference between the parts of encoder and decoder, in MF2ResU-Net, shortcut connections are used to combine the encoder and decoder layers in the blocks. To refine the feature of segmentation, atrous spatial pyramid pooling (ASPP) is embedded to achieve multi-scale features for the final segmentation networks.@*Results@#The MF2ResU-Net was superior to the existing methods on the criteria of sensitivity (Sen), specificity (Spe), accuracy (ACC), and area under curve (AUC), the values of which are 0.8013 and 0.8102, 0.9842 and 0.9809, 0.9700 and 0.9776, and 0.9797 and 0.9837, respectively for DRIVE and CHASE DB1. The results of experiments demonstrated the effectiveness and robustness of the model in the segmentation of complex curvature and small blood vessels.@*Conclusion@#Based on residual connections and multi-feature fusion, the proposed method can obtain accurate segmentation of retinal blood vessels by refining the segmentation features, which can provide another diagnosis method for computer-aided Chinese medical diagnosis.
ABSTRACT
Objective@#To investigate the geographical variation of prediabetes in adults in different regions of China, and to analyze the related factors of prediabetes.@*Methods@#Data was obtained from China Chronic Disease and Related Risk Factor Surveillance in 2013. The surveillance adopted multiple-stage stratified cluster random sampling method, which sampled 177 099 residents aged above 18 years old among 298 surveillance points in 31 provinces of Chinese Mainland. Questionnaire interview was used to obtain demographic variables, personal living style, and socio-economical information. Physical examination was conducted and fasting venous blood sample and (oral glucose tolerance test-2 hours, OGTT-2 h) venous blood sample were obtained from the participants. A total of 171 567 residents aged 18 and above were included in the analysis. The prevalence of prediabetes was analyzed by provinces and by China's geographical regions, after complex weighting. Multilevel logistic models were established to explore the related factors of prediabetes on the area level and individual level.@*Results@#The prevalence of prediabetes among residents aged 18 and above was 16.6% (95%CI: 15.6%-17.6%) in China. The prevalence of prediabetes was the highest (18.3%) in the south China and lowest (13.1%) in the northwest area. The difference of the prevalence in different areas were not statistically significant (P=0.510). If categorized the prevalence of prediabetes into 5 groups by quintile, Hainan, Jilin, Shandong, Anhui, Hunan and Chongqing were in the highest group of prevalence of prediabetes (18.6%-22.7%), and Tibet, Qinghai, Gansu, Ningxia, Guizhou, and Jiangxi were in the lowest group (7.6%-12.6%). The variance of prevalence of prediabetes on the county level (MOR: 1.60 (95%CI:1.53-1.67)) was more diverse than the province level (MOR: 1.21(95%CI:1.08-1.29)) and higher than the street level (1.23 (95%CI:1.14-1.30)). Several factors increased risk of pre-diabetes, including smoking, hazardous drinking and harmful drinking, drinking in the past 30 days, overweight, obesity, central obesity, sugary drink intake, hypertension, high total cholesterol, high triglycerides, high blood low-density lipoprotein cholesterol, low blood high-density lipoprotein cholesterol (all P<0.05). After adjusted the above variables, 92.5% of variance of prediabetes prevalence conld be explained on the provincial level.@*Conclusion@#The geographical distribution of prediabetes in adults in China differed by geographic areas, and it significantly varied on the county level. The related variables included demographic variables, personal behavior, and geographic related variables.
ABSTRACT
Objective To understand the status of oral health and its influencing factors among 12-year-old children in Chongqing, so as to provide evidence for setting up the intervention policy of oral health for children. Methods The data obtained from “the assessment on the comprehensive intervention effect for oral health among children in Chongqing” in 2015 were used in the present study; multi-level logistic regression model was used to analyze the status of oral health and its influencing factors among children in Chongqing. Results The prevalence of dental caries among 12-year-old children was 45. 5% (922/2 025) in Chongqing, and the status of oral health was clustered at school level (Ωu=0. 412, P=0. 091, α=0. 1). Multi-level logistic regression analysis indicated that the gender, sugar or chocolate intake once a week and above, and “whether children recognizing that oral health is very important for their life” were the individual variables affecting the dental caries incidence in 12-year-old children, and the difference between urban and rural schools was its background variable (P<0. 05, α=0. 05). Conclusion The gender, cognition to oral health, behavioral habit and the difference between urban and rural schools where children study are important factors influencing the oral health of 12-year-old children in Chongqing, and pertinent measures should be taken to improve the oral health among children.
ABSTRACT
A mortalidade infantil (MI) no Município de São Paulo (MSP) apresenta queda, principalmente a partir da década de 80, entretanto é possível que existam diferenças regionais importantes entre Subprefeituras uma vez que estas apresentam características sócio-ambientais que podem influenciar neste indicador. Objetivo - Descrever e analisar a evolução da MI no período de 2000 a 2007, segundo Subprefeituras do MSP. Métodos Estudo ecológico longitudinal, com 31 unidades de análise (Subprefeituras). Utilizou-se, para a análise estatística, o modelo de regressão linear multinível, considerando-se, como variável resposta, o eMI e oito anos de observação (2000 a 2007). O modelo incluiu variáveis relacionadas aos serviços de saúde. Resultados - A queda da MI não ocorre de modo homogêneo entre as Subprefeituras evidenciadas pelas diferentes inclinações das retas e interceptos observados e estimados. Após a análise pelo modelo multinível observou-se redução da MI no período de 18,8 por cento com declínio médio de 0,30 por cento nv ao ano Pelo modelo, 51 por cento da variabilidade da MI se explica por características contextuais das Subprefeituras. No período de estudo, o eMI aumenta: 0,056 por cento nv para cada 1 por cento de aumento na proporção de mães com pré-natal inadequado, 0,214 por cento nv para cada 1 por cento de aumento na proporção da população exclusivamente usuária SUS, 0,0390-oonv para cada aumento na taxa de leitos obstétricos SUS. O eMI diminui: 0,191 por cento nv para cada 1 por cento de aumento na proporção de recuperação da vitalidade do nv. Conclusão - A MI apresenta tendência de queda no período de 2000 a 2007 de modo não homogêneo segundo Subprefeitura. As variáveis que apresentaram associação com a MI são: o ano de observação, proporção de nascidos vivos de mães que realizaram até 6 consultas pré-natal (pré-natal inadequado); taxa de leitos obstétricos do Sistema Único de Saúde...
Introduction - Infant mortality (IM) in São Paulo (MSP) has declined, especially from the 80s. However, there may be important regional differences between Districts as their socio-environmental characteristics may influence this indicator. Objective - To describe and analyze IM trend in the period from 2000 to 2007, according to the Districts of MSP. Method - Ecological longitudinal study comprising 31 units of analysis (Districts). Linear multilevel regression model was used for statistical analysis. Infant Mortality Rate (IMR) and eight years of observation (2000-2007) were used as dependent variables. The model included variables related to health services. Results The decrease in IM does not occur homogeneously between Districts as evidenced by the different slopes and intercepts of the observed and estimated lines. A multilevel model showed an 18.8% reduction in IM in the period with an average decline of 0,300/00 living born (lb) per year. According to the model, 51% of the IM variability can be explained by contextual features of districts. During the study period, IMR increases: 0,0560/00lb for every 1% increase among mothers with inadequate prenatal care, 0,2140/00lb for every 1% increase among users of the Unified Health System (UHS), 0,0390/00lb for each increase in the UHS obstetric beds rate. IMR decreases 0,1910/00lb for every 1% increase in the vitality proportion of recovery of live births. Conclusion - IM shows a declining trend over the period from 2000 to 2007 in a non-homogeneous way according to District. The variables that were associated with IMR: year of observation, proportion of live births from mothers who had up to 6 prenatal visits (inadequate prenatal care), Unified Health System (UHS) obstetric beds rate, proportion of UHS users and vitality recovery of live birth proportion. The highest IMR is found in peripheral region of MSP where the largest proportion of UHS users is found.