Objective: To explore the SNP effects of patatin-like phospholipase domain which containing 3 (PNPLA3), transmembrane 6 superfamily member 2 (TM6SF2) gene, environmental effects of smoking, alcohol drinking and interaction between gene-gene, gene-environment and drinking-smoking on hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC). Methods: We collected anticoagulant peripheral blood from patients of HBV-HCC, chronic hepatitis B (CHB), liver cirrhosis (LC) and from healthy controls to detect the single nucleotide polymorphism (SNP) of patatin-like phospholipase domain containing 3 (PNPLA3) gene loci rs738409 and transmembrane 6 superfamily member 2 (TM6SF2) gene loci rs58542926, using the flight mass spectrometry method. The optimal assignment value of gene polymorphisms was defined by using the online SNP stats. Hardy-Weinberg (H-W) balance was tested for SNP. Effects of the genetic and environmental factors to HBV-HCC were analyzed by using the multiple classification logistic regression method. The gene-gene, gene-smoking and alcohol drinking interaction effects were investigated by Fork-Life analysis and binary logistic regression methods. Results: The frequency distribution of CHB group rs738409 loci seemed not in conformity with the H-W balance (χ(2)=11.980, P<0.005). Two loci frequency distributions in the other groups were all in accordandce with the H-W balance. After adjusting for influences on age and sex and comparing to the healthy group, the rs58542926 mutation appeared as OR=1.659, 95%CI: 1.026-2.684, P=0.039, in the HBV-HCC group. When comparing to CHB group, the HBV-HCC group presented that drinking as OR=1.680, 95%CI: 1.121-2.519, P=0.012. When comparing to the LC group, the ORs of drinking and smoking were 1.539 (1.071-2.213) and 1.453 (1.005-2.099) respectively, in the HBV-HCC group. When comparing to the CHB+LC group, interactions between the HBV-HCC group were found rs738409 and rs58542926 on additive model OR=1.548 (U=1.885, P=0.029) and OR=1.658 (P=0.024) on logistic regression model while drinking was rs738409 on interaction additive model with OR=1.811(U=1.965, P=0.024). As for drinking and mutation of rs738409, the multiplication model of logistic regression showed no statistically significant differences. Interaction between smoking and drinking appeared as OR=1.756 (P<0.001) in the logistics regression multiplication model. Conclusions: Factors as mutation of TM6SF2, smoking and drinking all appeared as risk factors for HBV-HCC. Mutations of both PNPLA3 and TM6SF2, together with smoking and drinking all served as risk factors for HBV-HCC. However, the mutation of single PNPLA3 appeared as a protective factor on HBV-HCC.
Alcohol Drinking/adverse effects* ; Carcinoma, Hepatocellular/virology* ; Case-Control Studies ; Epistasis, Genetic ; Gene-Environment Interaction ; Genetic Predisposition to Disease ; Genotype ; Hepatitis B virus ; Hepatitis B, Chronic ; Humans ; Lipase/genetics* ; Liver Cirrhosis, Alcoholic/complications* ; Liver Neoplasms/virology* ; Membrane Proteins/genetics* ; Polymorphism, Single Nucleotide ; Smoking/adverse effects*

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

BACKGROUNDThe metabolic syndrome is a clustering of metabolic abnormalities and has been associated with increased risk of type 2 diabetes mellitus and cardiovascular disease. This study aimed to estimate the prevalence of the metabolic syndrome among employees in Northeast China.

METHODSTotally, 33,149 employees who received health screening in the International Health Promotion Center in the First Hospital of Jilin University were enrolled. Height, weight, waist circumference, blood pressure, fasting plasma glucose, triglyceride, high-density lipoprotein, and low-density lipoprotein were recorded. Three definitions for the metabolic syndrome were applied, revised National Cholesterol Education Program's Adult Treatment Panel III (NCEP ATP III) criteria, the International Diabetes Federation (IDF) criteria, and the Chinese Diabetes Society (CDS) criteria.

RESULTSOverall, the age-standardized prevalence of the metabolic syndrome was 22.9%, 20.6%, and 15.3% based on definitions of revised NCEP ATP III criteria, the IDF criteria, and the CDS criteria, respectively. Men had higher age-standardized prevalence than women in all three definitions (P < 0.05). The prevalence was 27.1%, 24.5%, and 20.4% for men; 17.1%, 15.4%, and 8.3% for women, respectively. The most common metabolic component with the metabolic syndrome was overweight (54.7% of men had an elevated body mass index, and 35.9% of women had central obesity).

CONCLUSIONSA large proportion of employees among Northeast China have the metabolic syndrome. These findings place emphasis on the need to develop aggressive lifestyle modification for patients with the metabolic syndrome and population level strategies for the prevention, detection, and treatment of cardiovascular risk.

Blood Pressure ; physiology ; China ; epidemiology ; Female ; Humans ; Male ; Metabolic Syndrome ; epidemiology ; Obesity ; epidemiology ; Overweight ; epidemiology

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

Case-Control Studies ; Genetic Predisposition to Disease ; Genotype ; Hearing Loss, Noise-Induced ; Humans ; Male ; MicroRNAs ; Noise, Occupational ; Polymorphism, Single Nucleotide ; STAT3 Transcription Factor

Objective: To investigate the influence of dietary cholesterol intake on gestational diabetes mellitus (GDM), at one year prior to and first and second trimesters of pregnancy. Methods: Between March 2012 and September 2016, the pregnant women from the First Affiliated Hospital of Shanxi Medical University were asked to fill in a set of questionnaires, by which information on general demographic characteristics, diagnosis of GDM and dietary cholesterol intake was collected. Unconditional logistic regression method was used to analyze the influence of dietary cholesterol intake on GDM, at one year prior to and first and second trimesters of pregnancy. The association on dietary cholesterol intake and GDM between age groups was also analyzed. Results: Data on 9 005 subjects, including 1 388 pregnant women with GDM, was collected. When the amount of cholesterol intake was stratified into quartile, results from the unconditional logistic regression showed that dietary cholesterol intake appeared ≥76.50 mg/d, both in the periods of one year prior to and the second trimester of pregnancy. This amount of dietary cholesterol intake would increase the risk of GDM (one year prior to pregnant: OR=1.230, 95%CI: 1.018-1.485; second trimester: OR=1.228, 95%CI:1.014- 1.486). Women who took ≥76.50 mg/d of daily cholesterol during the period of one year prior to, or 46.75-76.50 mg/d during the second trimester of pregnancy, the risks of GDM (OR=4.644, 95%CI: 1.106-19.499) would increase. Women with daily cholesterol intake over 76.50 mg/d during the period of one year prior to or at the second trimester of pregnancy, there appeared a risk on GDM (OR=1.217, 95%CI: 1.012-1.463). When maternal age was divided in two different subgroups and the cholesterol intake level was ≥76.50 mg/d both in the period of one year prior to pregnancy or at the second trimester, the risk of GDM appeared in the subgroup of<35 years old (OR=1.336, 95%CI:1.083-1.647; OR=1.341, 95%CI: 1.087-1.654). However, no significant association was found in the maternal age group of ≥35 years old. Conclusion: High level of dietary cholesterol intake would increase the risk of GDM, both in the period of one year prior to and at the second trimester of pregnancy.
Adolescent ; Adult ; Asian People/statistics & numerical data* ; Cholesterol, Dietary ; Diabetes, Gestational/epidemiology* ; Female ; Humans ; Logistic Models ; Pregnancy ; Pregnancy Trimester, First ; Pregnancy Trimester, Second ; Risk Factors

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 estimate the incidence and mortality of kidney cancer in China in 2014, based on the cancer registration data. Data was collected through the National Central Cancer Registry (NCCR). Methods: All together, 449 cancer registries submitted required data on incidence and deaths of kidney cancer occurred in 2014, to the NCCR. After evaluation on the quality of data,339 registries were accepted for analysis and stratified by areas (urban/rural) and age groups. Combined with data from the National population in 2014, the nationwide incidence and mortality of kidney cancer were estimated. Data from the 2000 National census was used, and with Segi's population used for the rates of age-standardized incidence/mortality. Results: The qualified 339 cancer registries covered a total population of 288 243 347, with 144 061 915 in urban and 144 181 432 in rural areas. The percentage of morphologically verified cases and cases with only available death certificates were 72.70% and 1.27%, respectively. The mortality to incidence ratio was 0.37. The estimates of new cases were around 68 300 in whole China, in 2014, with a crude incidence rate as 4.99/100 000 (95%CI: 4.95/100 000-5.03/100 000). The age-standardized incidence rates of kidney cancer, estimated by China standard population (ASR China) and world standard population (ASR world) were 3.43/100 000 (95%CI: 3.40/100 000-3.46/100 000) and 3.40/100 000 (95%CI: 3.37/100 000- 3.43/100 000), respectively. The cumulative incidence rate of kidney cancer was 0.40% in China. The crude and ASR China incidence rates for males appeared as 6.09/100 000 (6.03/100 000-6.15/100 000) and 4.32/100 000 (4.28/100 000-4.36/100 000), respectively, whereas those were 3.84/100 000 (3.79/100 000-3.89/100 000) and 2.54/100 000 (2.50/100 000-2.58/100 000) for females. The crude and ASR China incidence rates in urban areas appeared as 6.60/100 000 (95%CI: 6.54/100 000-6.66/100 000) and 4.25/100 000 (95%CI: 4.21/100 000-4.29/100 000), respectively, whereas those were 3.05/100 000 (95%CI: 3.01/100 000-3.09/100 000) and 2.29/100 000 (95%CI: 2.25/100 000-2.33/100 000) in rural areas. The estimates of kidney cancer deaths were around 25 600 in the country, in 2014, with a crude mortality rate of 1.87/100 000 (95%CI: 1.85/100 000-1.89/100 000). The ASR China and ASR world mortality rates appeared as 1.16/100 000 (95%CI: 1.14/100 000-1.18/100 000) and 1.16/100 000(95%CI: 1.14/100 000-1.18/100 000), respectively, with a cumulative mortality rate (0-74 years old) of 0.12%. The crude and ASR China mortality rates were 2.31/100 000 (95%CI: 2.27/100 000- 2.35/100 000) and 1.52/100 000 (95%CI: 1.50/100 000-1.54/100 000) for males, respectively, whereas those were 1.41/100 000 (95%CI: 1.38/100 000-1.44/100 000) and 0.81/100 000 (95%CI: 0.79/100 000- 0.83/100 000) for females. The crude and ASR China mortality rates were 2.49/100 000 (95%CI: 2.45/100 000-2.53/100 000) and 1.42/100 000 (95%CI: 1.40/100 000-1.44/100 000) in urban areas, respectively, whereas those were 1.12/100 000 (95%CI: 1.09/100 000-1.15/100 000) and 0.78/100 000 (95%CI: 0.76/100 000-0.80/100 000) in the rural areas. Conclusions: Both the incidence and mortality of kidney cancer seemed low, in China. However, the incidence of kidney cancer had greatly increased. Our findings suggested that prevention and control strategies for kidney cancer should be focused on males in the urban areas.
Adolescent ; Adult ; Aged ; Child ; Child, Preschool ; China/epidemiology* ; Female ; Humans ; Incidence ; Infant ; Infant, Newborn ; Kidney Neoplasms/mortality* ; Male ; Middle Aged ; Registries ; Rural Population ; Urban Population ; Young Adult

Objective: To understand the prevalence of HIV infection and syphilis in clients in Ya'an of Sichuan province. Methods: A survey was conducted in clients recruited through snowball method in Ya'an of Sichuan from April 2014 to December 2015. The information of the clients, including basic demography characteristics, AIDS knowledge awareness, high-risk behaviors and others, were collected through face-to-face interviews. Blood sample (5 ml) was taken from each client to test antibodies against HIV and syphilis. Statistical software SPSS 18.0 was used for data analysis. Results: Among the 708 clients, the constituent ratio of those aged ≥50 years was 51.27% (363/708), those in Han ethnic group was 99.72% (706/708), those with junior high school educational level or below was 90.11% (638/708), those who got married or cohabitated with others was 74.15% (525/708), and those who used condoms at each sex was 27.40% (194/708). Seven HIV positive cases were detected and 4 cases were aged ≥50 years. Seven syphilis cases were detected and all the cases were aged ≥50 year. No HIV-syphilis co-infection case was detected. The prevalence of HIV infection and syphilis were all 0.99% (95%CI: 0.30%-1.70%). Results from the multivariate logistic regression analysis showed that the clients who had their first commercial sex behavior at age <30 years (OR=6.61, 95%CI: 1.09-40.18) would have higher HIV positive rate. Conclusion: The rate of condom use was low in the clients in Ya'an and they didn't pay enough attention to their self-protection in sexual activities. Especially the clients aged ≥50 years were with low educational level and had high risk commercial sexual behaviors for HIV infection and syphilis. Close attention needs to be paid to them.
Aged ; Coinfection/epidemiology* ; Condoms/statistics & numerical data* ; HIV Infections/ethnology* ; Humans ; Middle Aged ; Prevalence ; Risk Factors ; Sex Work ; Sexual Behavior/ethnology* ; Surveys and Questionnaires ; Syphilis/ethnology*

Objective: To study the relations between famine exposure and the risk of chronic diseases as diabetes mellitus, obesity, hypertension, coronary heart disease and stroke in the population of Harbin. Methods: Our data was collected from the baseline survey-the China Kadoorie Biobank project (CKB) in Harbin. Retrospective cohort study design was used. Related risks on chronic diseases including diabetes mellitus, obesity, hypertension, coronary heart disease and stroke, were compared among the famine exposed or non-exposed people, respectively by logistic analysis method. Results: After adjusted for factors as age, sex, physical activity, smoking, alcohol intake, diet, family history of diseases, it appeared that the factor 'famine exposure' had increased the risks of diseases as obesity (OR=1.204, 95%CI: 1.104-1.313, P<0.01), hypertension (OR=1.315, 95%CI: 1.210-1.429, P<0.01) and coronary heart disease (OR=1.495, 95%CI: 1.369-1.632, P<0.01). The lower the age of population being exposed to famine, the greater the risk of the development of all kinds of chronic diseases. Conclusions: Famine exposure appeared a risk factor for obesity, hypertension, and coronary heart disease. It is of great significance to ensure the life-long nutrition of the people, especially in the early and adolescent stages, to prevent obesity, hypertension, and coronary heart disease in their later lives.
Adolescent ; China/epidemiology* ; Chronic Disease/epidemiology* ; Coronary Disease/epidemiology* ; Diabetes Mellitus/epidemiology* ; Female ; Humans ; Hypertension/epidemiology* ; Obesity/epidemiology* ; Pregnancy ; Prenatal Exposure Delayed Effects/epidemiology* ; Retrospective Studies ; Socioeconomic Factors ; Starvation/epidemiology*