Male ; Humans ; Prostate/pathology* ; Adenocarcinoma/pathology* ; Giant Cells/pathology*

Alanine Transaminase ; Animals ; Carbon Tetrachloride ; Gastrointestinal Microbiome ; Liver/pathology* ; Liver Cirrhosis/pathology* ; Male ; Mice ; Mice, Inbred C57BL ; Quinazolines

Adult ; Brain ; Brain Diseases ; Heat Stroke ; Humans ; Magnetic Resonance Imaging ; Male ; Retrospective Studies

Cross-Sectional Studies ; Depression/epidemiology* ; Humans ; Job Satisfaction ; Occupational Stress/epidemiology* ; Oil and Gas Fields ; Stress, Psychological ; Surveys and Questionnaires

Objective: To describe the genetic structure of populations in different areas of China, and explore the effects of different strategies to control the confounding factors of the genetic structure in cohort studies. Methods: By using the genome-wide association study (GWAS) on data of 4 500 samples from 10 areas of the China Kadoorie Biobank (CKB), we performed principal components analysis to extract the first and second principal components of the samples for the component two-dimensional diagram generation, and then compared them with the source of sample area to analyze the characteristics of genetic structure of the samples from different areas of China. Based on the CKB cohort data, a simulation data set with cluster sample characteristics such as genetic structure differences and extensive kinship was generated; and the effects of different analysis strategies including traditional analysis scheme and mixed linear model on the inflation factor (λ) were evaluated. Results: There were significant genetic structure differences in different areas of China. Distribution of the principal components of the population genetic structure was basically consistent with the geographical distribution of the project area. The first principal component corresponds to the latitude of different areas, and the second principal component corresponds to the longitude of different areas. The generated simulation data showed high false positive rate (λ=1.16), even if the principal components of the genetic structure was adjusted or the area specific subgroup analysis was performed, λ could not be effectively controlled (λ>1.05); while, by using a mixed linear model adjusting for the kinship matrix, λ was effectively controlled regardless of whether the genetic structure principal component was further adjusted (λ=0.99). Conclusions: There were large differences in genetic structure among populations in different areas of China. In molecular epidemiology studies, bias caused by population genetic structure needs to be carefully treated. For large cohort data with complex genetic structure and extensive kinship, it is necessary to use a mixed linear model for association analysis.
China ; Genetic Structures ; Genome-Wide Association Study ; Humans ; Linear Models ; Principal Component Analysis

Objective: To evaluate the association of educational level with anthropometric measurements at different adult stages and their long-term changes in adults who participated in the second re-survey of China Kadoorie Biobank (CKB). Methods: The present study excluded participants who were aged >65 years, with incomplete or extreme measurement values, or with major chronic diseases at baseline survey or re-survey. The weight at age 25 years was self-reported. Body height, body weight and waist circumference at baseline survey (2004-2008) and re-survey (2013-2014) were analyzed. Results: The present study included 3 427 men and 6 320 women. Both body weight and waist circumference (WC) increased with age. From age 25 years to baseline survey (mean age 45.2±6.5), the mean weight change per 5-year was (1.70±2.63) kg for men and (1.27±2.10) kg for women. From baseline survey to re-survey (53.2±6.5), the mean changes per 5-year for body weight were (1.12±2.61) kg for men and (0.90±2.54) kg for women; and that for WC was (3.20±3.79) cm for men and (3.83±3.85) cm for women. Among women, low educational level was consistently associated with higher body mass index (BMI) and WC at age 25 years, baseline survey and re-survey. Among men, low educational level was associated with higher BMI at age 25 years. At baseline survey and re-survey, the educational level in men was not statistically associated with BMI; but men who completed junior or senior high school showed slight higher WC and increase of WC from baseline survey to re-survey than other male participants. Conclusions: Body weight and WC increased with age for both men and women. The associations of educational level with BMI and WC were different between men and women.
Adult ; Asian People/statistics & numerical data* ; Body Height ; Body Mass Index ; Body Weight ; China/epidemiology* ; Educational Status ; Female ; Humans ; Male ; Middle Aged ; Obesity/ethnology* ; Risk Factors ; Sex Distribution ; Waist Circumference/ethnology*

Objective: To understand the epidemiological and etiological characteristics of outbreaks on acute gastroenteritis caused by sapovirus (SaV) worldwide. Methods: Literature about the outbreaks on acute gastroenteritis caused by SaV were retrieved from the databases including WanFang, CNKI, PubMed and Web of Science after evaluation. Time, geography, setting and population distributions of outbreaks, transmission mode, SaV genotype and clinical characteristics of the patients were analyzed. Results: A total of 34 papers about SaV were included, involving 146 outbreaks occurred between October 1976 and April 2016. In these papers, 138 outbreaks were reported on the related months. All these outbreaks occurred in northern hemisphere. SaV outbreaks occurred all year around, but mainly in cold season, the incidence was highest in December (25 outbreaks) and lowest in in August (2 outbreaks). Most outbreaks were reported by Japan, followed by Canada, the United States of America and the Netherlands. There were 141 outbreaks for which the occurring settings were reported, child-care settings were most commonly reported setting (48/141, 34.04%), followed by long-term care facility (41/141, 29.08%) and hospital (16/141, 11.35%). Clinical symptoms of 1 704 cases in 31 outbreaks were reported, with the most common symptom was diarrhea (1 331/1 704, 78.12%), followed by nausea (829/1 198, 69.20%), abdominal pain (840/1 328, 63.25%), vomiting (824/1 704, 48.36%) and fever (529/1 531, 34.53%). Genotypes of SaV were determined for 119 outbreaks. GⅠ(51/119, 42.86%) and GⅣ (45/119, 37.82%) were predominant. The outbreaks of GⅣ SaV increased suddenly in 2007, and the outbreaks of GⅠ SaV mainly occurred in 2008 and during 2011-2013. Conclusions: SaV outbreaks were reported mainly by developed countries, with most outbreaks occurred in cold season, in child-care settings and long term care facility. GⅠ and GⅣ were the most common genotypes of SaV. Prevention and control of SaV outbreak in China seemed relatively weak, and it is necessary to conduct related training and to strengthen the SaV outbreak surveillance in areas where service is in need.
Caliciviridae Infections/virology* ; Child ; China/epidemiology* ; Disease Outbreaks ; Feces/virology* ; Gastroenteritis/virology* ; Genotype ; Humans ; Phylogeny ; RNA, Viral/genetics* ; Sapovirus/isolation & purification* ; Sequence Analysis, DNA

Objective: To analyze the prevalence and co-prevalence of cardio-metabolic related risk factors in farmers aged ≥18 years in China, to explore the influence of population economic factors on them. Methods: A total of 3 367 farmers, including fishermen or hunters, aged ≥18 years were selected as study subjects from the database of Nutritional Status and Health Transition of Chinese Residents Project in 2015. Basic information (age, gender), data on anthropometric (body height, weight and waist size), blood biochemical and socioeconomic (occupation, income, education level and living area) were included. According to the definition of the metabolic syndrome released by the International Diabetes Federation (IDF) in 2005, five cardio-metabolic risk factors appeared as central obesity, increased triglycerides, decreased HDL-C, increased blood pressure and increased plasma glucose. Co-prevalence of risk factors was defined as detecting 2 or more risk factors in a person at the same time. Multivariate logistic regression model was used to analyze the relationship between socioeconomic factors and metabolic risk factors. Results: In 3 367 framers of 15 provinces (autonomous region and municipality), the prevalence rates of central obesity, increased blood pressure, increased plasma glucose, increased triglycerides and decreased HDL-C were 51.8%, 59.0%, 17.0%, 25.5% and 38.7% respectively. Multivariate logistic regression analysis showed that the risks for central obesity (OR=3.69, 95%CI: 3.17-4.28) and decreased HDL-C (OR=3.28, 95%CI: 2.81- 3.82) were higher in women than in men, and the risks for increased blood pressure (OR=0.73, 95%CI: 0.63-0.84), increased blood glucose (OR=0.80, 95%CI: 0.67-0.97) were lower in women than in men. Age was positively correlated with the prevalence or co-prevalence of metabolic risk factors (trend P<0.05). Framers in western China had obviously lower risk for central obesity compared with farmers in central China. No significant correlation was found between farmers' income level, education level or the prevalence of metabolic risk factors. Conclusion: In 15 provinces of China, the prevalence of at least 1 kind of cardio-metabolic risk factor was found in 85.5% of the farmers, and the co-prevalence of cardio-metabolic risk factor was found in 60% of farmers. The prevalence and co-prevalence of cardio-metabolic risk factors were significantly associated with age and gender. It is suggested to take targeted nutritional intervention and health education according to the distribution characteristics of prevalence and co-prevalence of cardio-metabolic factors and strengthen the early prevention and control programs of the diseases.
Adolescent ; Adult ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Farmers ; Female ; Humans ; Male ; Metabolic Syndrome/epidemiology* ; Obesity/epidemiology* ; Prevalence ; Risk Factors

Objective: To describe the characteristics of cooking and heating fuel use in participants from the China Kadoorie Biobank (CKB) study. Methods: The CKB study recruited 512 891 adults from 10 areas in China during 2004-2008. Information on cooking fuel and heating fuel was collected using a questionnaire in baseline survey. The proportions of various fuels used in different areas, in different populations, and at different time points were calculated and compared. Results: Overall, 52.1% participants used solid fuel for cooking or heating. Rural areas had higher prevalence of solid fuel use than urban areas. The percentage of participants using solid fuel for cooking was 36.1% (coal 20.1%, wood/charcoal 16.0%); The percentage of participants using solid fuel for heating was 36.7% (coal 22.7%, wood/charcoal 14.0%). The prevalence of solid fuel use and the fuel type mainly used varied widely across 10 areas. The proportion of clean fuel use was lower in less-educated and lower-income people. Household coal and wood/charcoal use showed a declining trend, which was more remarkable in urban areas. Conclusion: There are still a large number of rural residents and people with low income relying on solid fuel in China, which is a serious public health concern.
Adult ; Air Pollution, Indoor ; China ; Coal ; Cooking ; Family Characteristics ; Humans ; Rural Population/statistics & numerical data* ; Urban Population/statistics & numerical data*