Objective: To explore the sampling method in China National Human Biomonitoring Program (HBP) and the related errors, so as to calculate and evaluate the study design in sampling. Methods: The sampling method of HBP is of multistage nature. Taking the results of sampling method from Guizhou province as an example, results related to sampling error and variation coefficient were calculated, using the multistage unequal probability sampling error method. Results: The HBP covered 152 monitoring sites in 31 provinces (autonomous regions and municipalities) and with 21 888 residents selected. The replacement rates at various stages were 5.26%, 6.35% and 40.6% respectively. The sampling error in Guizhou province was 3 207 594, and the coefficient of variation was 0.097. Conclusions: According to the multi-stage unequal probability sampling method, the sampling coefficient variability appeared small with high precision, in Guizhou province. However, this method did not consider the weight adjustment of non-sampling errors such as population missing rate and response rate. Methods related to the calculation on multi-stage sampling error among large-scale public health monitoring projects need to be further studied.
China ; Cities ; Environmental Monitoring ; Humans ; Research Design

Objective: To understand the seasonal distribution of patient hospitalization due to asthma exacerbation in 7 geographic areas in China. Methods: This was a retrospective study which involved patients hospitalized for asthma exacerbation in 29 hospitals throughout 7 geographic areas in the mainland of China (northeast, north, central, east, south, northwest and southwest). The numbers of asthmatic patients and total inpatients of the respiratory department of each hospital were recorded. The monthly ratio of asthmatic patients to the total inpatients in every area was calculated and compared. Results: During the study period, 6 480 patients were admitted for asthma exacerbation, accounting for 3.14% of all the 206 135 patients admitted to the respiratory departments in the 29 hospitals. The ratio of asthmatic patients to total inpatients in the northeast area (5.61%) was highest, and the ratio in east area was lowest (1.97%). Statistical analysis showed that the difference among different areas was significant (P<0.000 1). In most areas, both the number and proportion of hospitalized asthmatic patients peaked in spring (February-April) and autumn (September-October). In the northeast area, east area and south area, the peaks in spring were more obvious, while in the north area and southwest area, the peaks in autumn were more obvious. In the northwest area the peaks occurred in winter (December-January) and summer (June-August), respectively. The differences in hospitalization due to asthma among different months were significant in the northeast, north, and southwest areas (P<0.005). Conclusion: The number of patients hospitalized for asthma exacerbation fluctuated with season in different areas in China. In most areas, more asthmatic patients were admitted to hospitals in spring and autumn.
Asthma ; China/epidemiology* ; Hospitalization/statistics & numerical data* ; Humans ; Retrospective Studies ; Seasons

Objective: To explore the survival factors and construct a prognostic index (PI) for oral squamous cell carcinoma (OSCC). Methods: From January 2004 to June 2016, a total of 634 patients with pathologically confirmed OSCC were recruited in a hospital of Fujian. The clinical and follow-up data of all the patients with pathologically confirmed OSCC were collected to identify the factors influencing the prognosis of OSCC. All the patients were randomly divided into two groups: modeling group (modeling dataset, n=318) and validation group (validation dataset, n=316). Randomization was carried out by using computer-generated random numbers. In the modeling dataset, survival rates were calculated using Kaplan-Meier method and compared using the log-rank test. Cox regression model was used to estimate the hazard ratio (HRs) and 95% confidence intervals (CIs) of prognosis factors. An PI for OSCC patients prognostic prediction model was developed based on β value of each significant variable obtained from the multivariate Cox regression model. Using the tertile analysis, patients were divided into high-risk group, moderate-risk group, and low-risk group according to the PI, the Akaike information criterion (AIC) and Harrell's c-statistic (C index) were used to evaluated the model's predictability. Results: Results from the multivariate Cox regression model indicated that aged ≥55 years (HR=2.22, 95%CI: 1.45-3.39), poor oral hygiene (HR=2.12, 95%CI: 1.27-3.54), first diagnosis of lymph node metastasis (HR=5.78, 95%CI: 3.60-9.27), TNM stage Ⅲ-Ⅳ (stage Ⅰ as reference) (HR=2.43, 95%CI: 1.10-5.37) and poor differentiation (well differentiation as reference) (HR=2.53, 95%CI: 1.60-4.01) were the risk factors influencing the prognosis of OSCC. The PI model had a high predictability in modeling group and validation group (AIC and C index were 1 205.80, 0.700 2 and 1 150.47, 0.737 3). Conclusion: Age, poor oral hygiene, first diagnosis of lymph node metastasis, TNM stage and histological grade were factors associated with the prognosis of OSCC, and the PI model has a certain significance in the clinical treatment of OSCC.
Carcinoma, Squamous Cell/therapy* ; China/epidemiology* ; Humans ; Lymphatic Metastasis ; Middle Aged ; Mouth Neoplasms/therapy* ; Prognosis ; Proportional Hazards Models ; Risk Factors ; Survival Rate ; Treatment Outcome