The China National Health Survey (CNHS) is the first nationwide multi-ethnic cross-sectional interview and health examination conducted from 2012 to 2017. The survey is designed to study reference intervals for physiological constants as well as determinants of noncommunicable diseases among different ethnic populations in different areas, so that the data can be used to enhance clinical diagnosis strategies and health promotion. CNHS used a stratified, multistage cluster sampling method to obtain a sample of 53 895 people aged 20-80 years in 10 ethnic groups from 11 provinces or autonomous regions all over China. Blood samples were collected from each participant for the establishment of the China Multi-Ethnic Biobank (CMEB). CNHS collected data on demographic and socioeconomic information, lifestyle factors, anthropometric measures, laboratory tests and clinical profiles. These data provide a comprehensive resource for further study on risk factors of noncommunicable disease among different ethnic groups. Information about the CNHS database, including publication list, introduction of the survey design and methods, and guidelines for submitting electronic forms of data application, is available at [http://www.bmicc.cn/web/share/home].

Introduction: The prevalence of hyperuricemia is increasing world widely; the understanding of population attributable faction of modifiable risk factors is important for disease prevention. Given the sparse evidence on how modifiable risk factors influence hyperuricemia in mainland China, we aim to explore the effect of excess weight and alcohol consumption and the population attributable fractions of hyperuricemia based on a national survey in mainland China. Methods: Using data from China National Health Survey which included 31746 Han Chinese aged 20-80 from ten provinces, we estimated the prevalence and modifiable risk factors (overweight/obesity and alcohol consumption)of hyperuricemia. Hyperuricemia was defined as serum uric acid > 417 μmol/L in men and > 340 μmol/L in women. Restricted cubic spline models were used to demonstrate the linear and non-linear association between exposures and hyperuricemia. The adjusted population attributable risk (PAR) was calculated to understand the relative importance of each modifiable risk factor. Results: The prevalence of hyperuricemia was 25.1% in men and 15.9% in women. The population fraction of hyperuricemia cases that could be avoided by weight loss was 20.6% (19.2% to 22.0%) in men and 18.1% (17.1% to 19.0%) in women. The PAR of alcohol consumption was 12.8% (8.5% to 17.1%) in men. Participants from southwest China had the highest hyperuricemia prevalence (47.9% in men and 29.9% in women), but with lower PAR of modifiable risk factors, especially in men (16.7%). Subjects in North China had lower hyperuricemia prevalence but higher PAR of modifiable risk factors. 44.8% male hyperuricemia cases in Inner Mongolia (26.9% of hyperuricemia prevalence) and 37.7% cases in men from Heilongjiang (34.4% of hyperuricemia prevalence) were attributable to overweight/obesity and alcohol consumption. Conclusion: There are significant sex and geographic difference on population attributable risk of hyperuricemia due to modifiable risk factors. More tailored prevention strategies are needed to prevent hyperuricemia through weight loss and the reduction of alcohol consumption.

Objective: To estimate the prevalence of diabetes and identify risk factors in the Uyghur and Han population in Xinjiang, China. Methods: A cross-sectional study in urban and rural areas in Xinjiang, including 2863 members of the Uyghur population and 3060 of the Han population aged 20 to 80 years, was conducted from June 2013 to August 2013. Data on fasting plasma glucose (FPG) and personal history of diabetes were used to estimate the prevalence of diabetes. Data on demographic characteristics, lifestyle risk factors, and lipid profiles were collected to identify risks factors using the multivariate logistic regression model. Results: In urban areas, the age- and gender-standardized prevalence of diabetes was 8.21%, and the age- and gender-standardized prevalence of diabetes was higher in the Uyghur population (10.47%) than in the Han population (7.36%). In rural areas, the age- and gender-standardized prevalence of diabetes was 6.08%, and it did not differ significantly between the Uyghur population (5.71%) and the Han population (6.59%). The results of the multivariate logistic regression analysis showed that older age, obesity, high triglycerides (TG), and hypertension were all associated with an increased risk of diabetes in the Uyghur and Han population. Urban residence and low high-density lipoprotein cholesterol (HDL-C) were associated with an increased risk of diabetes in the Uyghur population. Being an ex-drinker was associated with an increased risk of diabetes and heavy physical activity was associated with a decreased risk of diabetes in the Han population. Conclusions: Our study indicates that diabetes is more prevalent in the Uyghur population compared with the Han population in urban areas. Strategies aimed at the prevention of diabetes require ethnic targeting.

Background: The effects of the fat-to-muscle ratio (FMR) on hyperuricemia and a reduction in the estimated glomerular filtration rate (eGFR) are still unclear. Methods: Data from the China National Health Survey were used to explore the associations of the FMR with hyperuricemia and reduced eGFR. The fat mass and muscle mass were measured through bioelectrical impedance analysis. Mediation analysis was used to estimate the mediated effect of hyperuricemia on the association between the FMR and reduced eGFR. Results: A total of 31171 participants were included. For hyperuricemia, compared with the Q1 of the FMR, the ORs (95% CI) of Q2, Q3 and Q4 were 1.60 (1.32–1.95), 2.31 (1.91–2.80) and 2.71 (2.15–3.43) in men and 1.91 (1.56–2.34), 2.67 (2.12–3.36) and 4.47 (3.40–5.89) in women. For the reduced eGFR, the ORs (95% CI) of Q2, Q3 and Q4 of the FMR were 1.48 (1.18–1.87), 1.38 (1.05–1.82) and 1.45 (1.04–2.04) in men aged 40–59, but no positive association was found in younger men or in women. Hyperuricemia mediated the association between the FMR and reduced eGFR in men. The OR (95% CI) of the indirect effect was 1.08 (1.05–1.10), accounting for 35.11% of the total effect. Conclusions: The FMR was associated with hyperuricemia and reduced eGFR, and the associations varied based on sex and age. The effect of the FMR on the reduced eGFR was significantly mediated by hyperuricemia in men.

Adiposity and alcohol consumption are reported to be associated with a higher level of serum uric acid (SUA), but whether their effect differs on SUA percentile distribution is still unclear. In this study, we aimed to investigate how alcohol intake and body fat percentage (%BF) integrated with body mass index (BMI) influence the distribution of SUA in Chinese adults. Data from the China National Health Survey (CNHS) which included adults from 10 provinces of China were used (n = 31,746, aged 20–80 years, 40% male). %BF and BMI were integrated into eight expanded body composition groups to understand how excess body adiposity affects the distribution of SUA in the populational level. Self-report alcohol intake information was collected by face-to-face questionnaire interview. Quantile regression (QR) was used to analyze the data. We found that adiposity and alcohol consumption were associated with SUA, especially at the upper percentile in both sexes. In obese men, the QR coefficients at the 75th and 95th percentiles were 74.0 (63.1–84.9) and 80.9 (52.5–109.3) μmol/L, respectively. The highest quartile of %BF in men had a 92.6 (79.3–105.9) μmol/L higher SUA levels at its 95th percentile than the 5th quartile (p < 0.001). Compared with normal or underweight with the lowest %BF group (NWBF1), the obesity-highest %BF group (OBBF4) had the strongest positive effect on SUA, especially at the higher percentile of SUA. In BMI-defined normal or underweight participants, a higher quartile of %BF had greater effect size in all SUA percentiles. In men, current alcohol drinking had the strongest effect at the 95th percentile of SUA (QR coefficient: 31.8, with 95% CI: 22.6–41.0) comparing with 14.5, 95% CI of 8.4 to 20.6 in the 5th SUA percentile. High risk of alcohol consumption had a greater effect on SUA, especially in the higher SUA percentile. The observation of stronger association at the higher percentile of SUA suggests that decreasing body adiposity and alcohol intake at the populational level may shift the upper tails of the SUA distributions to lower values, thereby reducing the incidence of hyperuricemia.