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 estimate the incidence and distribution characteristics of fall related injury in people aged ≥50 years in 8 provinces in China and related physiological, psychological and social risk factors. Methods: Cross-sectional data were collected from adults aged ≥50 years participating in the World Health Organization (WHO) study on global ageing and adult health (SAGE) round 1 in China. Two-level hierarchical logistic model was used to identify the related factors for fall-related injury. All the models were stratified by living area (urban/rural). Results: Estimated incidence of fall related injury (road traffic injury was not included) was 3.2%. Ageing and multiple chronic conditions (OR=2.55, 95%CI: 1.41-4.64) was significantly associated with the incidence of fall related injury in urban area. In rural area, depression (OR=4.33, 95% CI: 2.52-7.42) and multiple chronic conditions (OR=2.46, 95%CI: 1.37-4.41) were associated with the incidence of fall related injury. Conclusions: This study estimated the incidence of fall related injury in adults aged ≥50 years in 8 provinces in China. A significant association between multiple chronic conditions and fall related injury were found in both urban and rural residents. Targeted measures should be taken for the prevention and control of chronic diseases in elderly population.
Accidental Falls/statistics & numerical data* ; Aged ; China ; Chronic Disease/epidemiology* ; Cross-Sectional Studies ; Depression/epidemiology* ; Humans ; Incidence ; Logistic Models ; Middle Aged ; Risk Factors ; Rural Population ; Wounds and Injuries/etiology*

Objective: To assess the association and intensity of baseline TC level with the incidence of lung cancer in men in China. Methods: Since May 2006, all the male workers, including the employees and the retirees in Kailuan Group were recruited in the Kailuan male dynamic cohort study. Information about demographics, medical history, anthropometry and TC level were collected at the baseline interview, as well as the information of newly-diagnosed lung cancer cases during the follow-up period. According to guidelines for blood lipids in Chinese adults and the distribution in the population, TC level was classified into five groups as followed: <160, 160-, 180-, 200- and ≥240 mg/dl, with the second quintile group (160- mg/dl) serving as the referent category. Cox proportional hazards regression model and restricted cubic spline (RCS) model were used to evaluate the association and the nonlinear association between baseline TC level and the risk of lung cancer in the men. Results: By December 31, 2014, for the 109 884 men, a follow up of 763 819.25 person-years was made with a median follow-up period of 7.88 years. During the follow up, 808 lung cancer cases were identified. After adjustment for age, education level, income level, smoking status, alcohol consumption level, history of dust exposure, FPG level and BMI, HR (95%CI) of lung cancer for men with lower TC level (<160 mg/dl) and higher TC level (≥240 mg/dl) were 1.34 (1.04- 1.72) and 1.45 (1.09-1.92), respectively, compared with men with normal TC level (160- mg/dl). The results didn't change significantly after exclusion of newly diagnosed cancer cases within 2 years of follow up and subjects with the history of hyperlipidemia. Conclusion: Our results showed that TC might be associated with higher risk of lung cancer. Men with lower TC level or higher TC level had higher risk for lung cancer. Keep moderate TC level might be one of the effective precaution for the prevention of lung cancer.
Adult ; Asian People ; China/epidemiology* ; Cholesterol/blood* ; Cohort Studies ; Humans ; Incidence ; Lipids ; Lung Neoplasms/ethnology* ; Male ; Proportional Hazards Models ; Prospective Studies ; Risk Factors

Objective: To study the prevalence and characteristics of overweight and obesity among Chinese children aged 0-5 years, in 2010-2013. Methods: Data was from the'China Nutrition and Health Surveillance-0-5-Years-Old Children and Lactating Women'project in 2013. Stratified multistage cluster sampling method was used to select 55 districts/counties from 30 provinces (autonomous regions, municipalities) with the sample size of children as 32 862. Definition of overweight and obesity were according to both the WHO 2006 growth standard in children less than 5-year-old and the WHO 2007 growth reference in children of 5-years-old. Results: were calculated by complex weight based on national census from the National Bureau of Statistics in 2010. Results The overall prevalence of overweight was 8.4% among the 0-5-year-old in 2013, with 9.4% in boys and 7.2% in girls. Both of the rates from urban and rural areas were the same, as 8.4%. The prevalence rates of overweight in the 0-, 6-, 12-, 24-, 36-, 48- and 60-71 months age groups appeared as 13.0%, 11.1%, 8.3%, 6.0%, 4.8%, 3.9% and 15.9%, respectively. The rates of overweight in low, medium and high income families were 8.0%, 8.8% and 8.9%, respectively. The prevalence of obesity was 3.1% among the 0-5-year-old, with 3.6% in boys and 2.5% in girls. There was no significant difference seen in urban (3.3%) and rural areas (2.9%). The prevalence rates for obesity in the 0-, 6-, 12-, 24-, 36-, 48- and 60-71 months age groups were 5.8%, 3.8%, 2.5%, 1.6%, 1.2%, 1.3% and 7.8%, respectively. The rates of obesity in low, medium and high income families were 2.8%, 3.3% and 3.5%, respectively. Conclusion: The prevalence rates of both overweight and obesity were increasing among the 0-5-year-olds in China, suggesting that it is necessary to timely conduct the surveillance and intervention programs on overweight and obesity in this target population.
Adolescent ; Asian People/statistics & numerical data* ; Body Mass Index ; Body Weight ; Child ; Child, Preschool ; China/epidemiology* ; Female ; Humans ; Income ; Infant ; Infant, Newborn ; Lactation ; Male ; Nutritional Status ; Obesity/ethnology* ; Overweight/ethnology* ; Prevalence

Shanghai Diet and Health Survey (SDHS) was designed to prospectively access local residents' food consumption, energy and nutrient intake, related chemical contaminant exposure, and the seasonal change trend to explore the relationship of diet with health. Data from SDHS can be used as fundamental information and scientific evidences for the development of local nutrition and food safety policies.
China ; Diet ; Energy Intake ; Health Surveys ; Nutrition Policy ; Nutrition Surveys

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