ABSTRACT
Objective To describe the current situation of diarrhea in children under five years old in Nepal and to explore its influencing factors. Methods Data were collected from the open-access database, Nepal Demographic and Health Surveys in 2006, 2011 and 2016. Chi-square ( 2) and Wilcoxon rank sum test were used to compare difference of potential risk factors between groups with and without diarrhea. Multiple Logistic regression model was adopted to identify significant influencing factors on diarrhea in children under five years old in Nepal. Results In 2006, 2011 and 2016, the incidence of diarrhea children under five in Nepal was 12.3%, 13.3% and 6.8%, respectively. Univariate analysis of the potential influencing factors showed that there were significant differences in the gender, water source, toilet facilities and fuel type, age of children, age of mother when she gave birth to the child and education years of mother and children with and without diarrhea (all P＜0.05). Multiple analysis revealed that improved toilet facilities (OR=0.874, 95% CI: 0.769-0.994, P=0.041) and the age of children(OR=0.613, 95% CI: 0.580-0.645, P＜0.001) were protective factors of childhood diarrhea, and the risk of boys was higher than that of girls(OR=1.277, 95% CI: 1.147-1.423, P＜0.001). Conclusions From 2006 to 2016, the incidence of diarrhea in children under five years old in Nepal was decreasing. Toilet facilities, age of children and gender of children were identified as the influencing factors of childhood diarrhea.
ABSTRACT
Objective: To build a model to predict critically ill-patients with coronavirus disease 2019 (COVID-19), and provide a new idea for the rapid identification of clinical progression in the early stage of critically ill-patients. Methods: A retrospective analysis of the general data of 152 general patients and 323 critically ill-patients diagnosed with COVID-19 from Jan 17th, 2020 to Feb 25th, 2020 in Wuhan Third Hospital was carried out; At the same time, the differences in fever, blood routine, liver and kidney function, coagulation function, C-reactive protein (CRP), and nucleic acid reagent testing results from the day of admission were statistically analyzed. Factors with statistical significance were included in a multivariate logistic regression analysis to obtain independent relevant factors that affect the critical ill-patients with COVID-19. Then a prediction model was built based on these factors and its accuracy was evaluated by the receiver operating characteristic (ROC) curve. Results: The sensitivities of age, fever, neutrophil ratio, lymphocyte ratio, serum creatinine (Scr) and combined diagnosis were 0.664, 0.671, 0.607, 0.669, 0.302 and 0.710, respectively; The specificities were 0.669, 0.585, 0.795, 0.685, 0.895 and 0.802, respectively; The area under the curve (AUC) were 0.725, 0.628, 0.721, 0.681, 0.590 and 0.795, respectively; The AUC of combined diagnosis was higher than that of single diagnosis (P < 0.05). Conclusion: The logistic regression and combined with ROC curve model based on multi-factors, including age, fever status, neutrophil ratio, lymphocyte ratio, and Scr, can play a good role in predicting the occurrence of critically ill-patients with COVID-19, which is worthy of further promotion and application.
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Objective To investigate the risk factors of adult urolithiasis in China. Methods 14 areas including 11 communities and 19 villages were randomly selected from 7 provinces of China by multi-stage stratified cluster sampling method during the period of May 2013 to July 2014. Individuals were investigated by a face-to-face questionnaire and a physical examination including urinary tract ultrasonographic examinations, routine blood and urine tests and blood biochemical examination ect. Results In total, 1 447 participants were found with the urolithiasis among 9 310 individuals and the overall prevalence was 15.5% (1 447/9 310). The prevalence of urolithiasis was significantly different among 14 areas ( 2=711.523，P<0.001), the lowest was the village in Shanxi (0.76%) and the highest was the village in Guangdong(35.99%). The intercept-only model further indicated the reginal aggregation for the individuals of urolithiasis (t=2.48, P=0.027) and the ICC was 48.74%. The two-level Logistic regression model showed that the gender (OR=1.235, 95% CI:1.082-1.411, P=0.005), age (OR=1.101, 95% CI:1.047-1.158, P=0.001), diabetes mellitus (OR=1.411，95%CI:1.192-1.670, P=0.001), family history of urinary calculi (OR=1.867, 95% CI:1.500-2.323, P<0.001), LDL (OR=1.150, 95% CI:1.050-1.260, P=0.006), drinking coffee (OR=1.352, 95% CI:1.065-1.716, P=0.017) and drinking sodas (OR=1.547, 95% CI:1.203-1.990, P=0.002) were the risk factors for urolithiasis. By contrast, consumed more fermented vinegar (OR=0.567, 95% CI:0.498-0.645, P<0.001) and had a amount of legume (OR=0.726, 95% CI:0.628-0.839, P<0.001) were protective factors of urolithiasis. Conclusion The prevalence of urolithiasis among adults reveal an aggregation in area-level, influenced by life environment and dietary habits of individual.