Objective:To describe the distribution of lipoprotein (a) [Lp(a)] levels in non-arteriosclerotic cardiovascular disease (ASCVD) population in China and explore its influencing factors.Methods:This study was based on a nested case-control study in the CKB study measured plasma biomarkers. Lp(a) levels was measured using a polyclonal antibody-based turbidimetric assay certified by the reference laboratory and ≥75.0 nmol/L defined as high Lp(a). Multiple logistic regression model was used to examine the factors related to Lp(a) levels.Results:Among the 5 870 non-ASCVD population included in the analysis, Lp(a) levels showed a right-skewed distribution, with a M ( Q1, Q3) of 17.5 (8.8, 43.5) nmol/L. The multiple logistic regression analysis found that female was associated with high Lp(a) ( OR=1.23, 95% CI: 1.05-1.43). The risk of increased Lp(a) levels in subjects with abdominal obesity was significantly reduced ( OR=0.68, 95% CI: 0.52-0.89). As TC, LDL-C, apolipoprotein A1(Apo A1), and apolipoprotein B(Apo B) levels increased, the risk of high Lp(a) increased, with OR (95% CI) for each elevated group was 2.40 (1.76-3.24), 2.68 (1.36-4.93), 1.29 (1.03-1.61), and 1.65 (1.27-2.13), respectively. The risk of high Lp(a) was reduced in the HDL-C lowering group with an OR (95% CI) of 0.76 (0.61-0.94). In contrast, an increase in TG levels and the ratio of Apo A1/Apo B(Apo A1/B) was negatively correlated with the risk of high Lp(a), with OR (95% CI) of 0.73 (0.60-0.89) for elevated triglyceride group, and OR (95% CI) of 0.60 (0.50-0.72) for the Apo A1/B ratio increase group (linear trend test P≤0.001 except for Apo A1). However, no correlation was found between Lp(a) levels and lifestyle factors such as diet, smoking, and physical activity. Conclusions:Lp(a) levels were associated with sex and abdominal obesity, but less with lifestyle behaviors.

AIM: To understand the current status and differences in visual acuity of children of the same age from different regions of Xi'an, and to take an effective basis for the prevention of children's myopia.METHODS: Random stratified sampling was used to select the uncorrected distance visual acuity and computed dioptric data of 41 285 children aged 6-12 from 6 towns, 10 urban and rural areas and 112 country schools screened by Xi'an Central Hospital in December 2022.RESULTS: The myopia detection rate in different regions of Xi'an is 47.16% in towns, 38.59% in urban and rural areas, and 32.29% in the country, and the total myopia rate is 37.50%. The myopia rate of 6-12 years old in towns is higher than that in urban and rural areas, and that of urban and rural areas is higher than that of country; the myopia rate of girls is higher than that of boys; myopia rate increases with age; mild myopia: the myopia rate in towns is significantly higher than that of the urban and rural areas and the country; high myopia: the myopia rate in the country is significantly higher than that of the towns and the urban and rural areas. The total rate of deficient hyperopia reserves in different regions of Xi'an is 92.08% in towns, 93.67% in urban and rural areas, and 90.92% in the country, and the total rate of deficient hyperopia reserves is 92.09%. The rate of deficient hyperopia reserves at the age of 6-12 is higher in the urban and rural areas than in the towns, and higher in the towns than in the country; the total rate of deficient hyperopia reserve is higher in girls than in boys; it is the peak period of the development of hyperopia reserve rate before the age of 8.CONCLUSION: The total myopia rate and the total vision reserve deficiency rate of 6-12 years old in different regions of Xi'an are different, and 8-9 years old is the accelerated period of myopia development, and the peak of deficient hyperopia reserve is before the age of 8 years old. With the growth of age, the myopia rate shows a certain growth trend, and the rate of deficient hyperopia reserve shows a decreasing trend after reaching the peak. The total myopia rate and insufficient acuity reserve rate of girls are higher than those of boys.

Objective:To investigate the relationship between chronic obstructive pulmonary disease (COPD) and bone mineral density (BMD) in Chinese male and female adults.Methods:Linear regression models were used to analyze the correlations between COPD and the Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade concerning bone mineral density indices, including broadband ultrasound attenuation, speed of sound, and stiffness index, based on data from the second resurvey of China Kadoorie Biobank.Results:Among 23 876 participants, the prevalence of COPD was 34.3% (3 130/9 125) in males and 23.2% (3 416/14 751) in females. Compared with healthy males and healthy females, broadband ultrasound attenuation, speed of sound, and stiffness index decreased in males and females with COPD, with β values (95% CI) of -0.87 (-1.37- -0.36), -3.42 (-5.42- -1.43) and -1.53 (-2.34- -0.71) in males and -0.66 (-1.09- -0.23), -2.24 (-3.92- -0.55), -1.06 (-1.71- -0.40) in females, respectively. The decrease was greater in males than females (all P for interaction <0.05). The GOLD grade of COPD was inversely correlated with all the three indices in a dose-response manner (all P for trend <0.001). Subgroup analysis showed that patients with COPD had a greater decrease in BMD in males whose ages were ≥ 60 years, males who were less physically active, and participants who were not overweight or obese. Conclusions:COPD was negatively correlated with bone mineral density. More attention should be paid to the bone mineral density of patients with COPD, especially those with older age, less physical activity, or lower BMI.

BACKGROUND: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. METHODS: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately. RESULTS: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. CONCLUSIONS In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.
Male ; Humans ; Female ; Coronary Artery Disease/genetics* ; Biological Specimen Banks ; East Asian People ; Risk Assessment/methods* ; Genetic Predisposition to Disease/genetics* ; Risk Factors ; Genome-Wide Association Study

BACKGROUND: Existing evidence suggests that fruit consumption is a significant influencing factor for chronic obstructive pulmonary disease (COPD), but this is unclear in the Chinese population. We examined the association of fresh fruit consumption with the risk of COPD-related hospitalization and death in a nationwide, population-based prospective cohort from China. METHODS: Between 2004 and 2008, the China Kadoorie Biobank recruited >0.5 million adults aged 30 to 79 years from ten diverse regions across China. After excluding individuals diagnosed with major chronic diseases and prevalent COPD, the prospective analysis included 421,428 participants. Cox regression was used to calculate the hazard ratios (HRs) for the association between fresh fruit consumption and risk of COPD-related hospitalization and death, with adjustment for established and potential confounders. RESULTS: During a mean follow-up of 10.9 years, 11,292 COPD hospitalization events and deaths were documented, with an overall incidence rate of 2.47/1000 person-years. Participants who consumed fresh fruit daily had a 22% lower risk of COPD-related hospitalization and death compared with non-consumers (HR = 0.78, 95% confidence interval [CI]: 0.71-0.87). The inverse association between fresh fruit consumption and COPD-related hospitalization and death was stronger among non-current smokers and participants with normal body mass index (BMI) (18.5 kg/m 2 ≤ BMI < 24.0 kg/m 2 ); the corresponding HRs for daily fresh fruit consumption were 0.78 (95% CI: 0.68-0.89) and 0.69 (95% CI: 0.59-0.79) compared with their counterparts, respectively. CONCLUSIONS High-frequency fruit consumption was associated with a lower risk of COPD in Chinese adults. Increasing fruit consumption, together with cigarette cessation and weight control, should be considered in the prevention and management of COPD.

Background:It remains unclear about the association of muscle mass, strength, and quality with death in the general Chinese population of diverse economical and geographical backgrounds. The present study aimed to comprehensively examine such associations across different regions in China.Methods:Based on the China Kadoorie Biobank study, the present study included 23,290 participants who were aged 38 to 88 years and had no prevalent cardiovascular diseases or cancer. Muscle mass and grip strength were measured using calibrated instruments. Arm muscle quality was defined as the ratio of grip strength to arm muscle mass. Low muscle mass, grip strength, and arm muscle quality were defined as the sex-specific lowest quintiles of muscle mass index, grip strength, and arm muscle quality, respectively. Cox proportional hazards models yielded hazard ratios (HRs) and 95% confidence intervals (CIs) for risks of all-cause mortality in relation to muscle mass, strength, and quality.Results:During a median follow-up of 3.98 years, 739 participants died. The HR (95% CI) of all-cause mortality risk was 1.28 (1.08-1.51) for low appendicular muscle mass index, 1.38 (1.16-1.62) for low total muscle mass index, 1.68 (1.41-2.00) for low grip strength, and 1.41 (1.20-1.66) for low arm muscle quality in models adjusted for sociodemographic characteristics, lifestyle factors, and medical histories.Conclusion:Low muscle mass, grip strength, and arm muscle quality are all associated with short-term increased risks of mortality, indicating the importance of maintaining normal muscle mass, strength, and quality for general Chinese adults.

Objective:To describe the prevalence of daytime nap habit in participants of the China Kadoorie Biobank (CKB) study, across 10 study regions and explore its correlation with prevalence of major chronic diseases.Methods:Participants with a self-reported pre-diagnosis of any cancer at baseline survey were excluded. Logistic regression models were used to analyze the differences in study regions and age distribution of the prevalence daytime nap habit, and its correlation with the prevalence of diabetes, hypertension, coronary heart disease (CHD), stroke, chronic obstructive pulmonary disease (COPD), and chronic liver diseases.Results:Among 510 145 participants, 39.9% had daytime nap habit in summer and 20.8% had daytime nap habit all the year round. Urban-rural differences were observed in the prevalence of summer nap habit and perennial nap habit. Daytime nap in summer was common in rural areas and Suzhou, with prevalence ranged from 32.9% to 73.3%. Haikou and Liuzhou had higher prevalence of perennial nap (60.4% and 63.3%). The proportion of people with daytime nap habit all the year round increased with age ( P for trend <0.001), the proportion was highest in those aged 70- years (31.9%). Daytime nap habit in summer was positively correlated with the prevalence of diabetes, hypertension, CHD and chronic liver disease with OR of 1.10 (95% CI: 1.07-1.14), 1.03 (95% CI:1.02-1.05), 1.07 (95% CI: 1.02-1.12) and 1.07 (95% CI:1.00-1.14), respectively. Daytime nap habit all the year round was positively correlated with the prevalence of diabetes, hypertension, CHD, stroke, COPD and chronic liver disease with OR of 1.33 (95% CI: 1.29-1.37), 1.11 (95% CI: 1.09-1.13), 1.39 (95% CI: 1.33-1.45), 1.33 (95% CI: 1.26-1.41), 1.12 (95% CI: 1.08-1.16) and 1.27 (95% CI:1.18-1.37) respectively. Conclusion:There were regional and age differences in prevalence of daytime nap habit among CKB participants. Daytime nap habit, especially daytime nap habit all the year round, was positively correlated with the prevalence of major chronic diseases.

Objective:To investigate the prevalence and influencing factors of xerosis in elderly inpatients, to provide basis for effective prevention and management of xerosis.Methods:Using the cross-sectional survey method and the self-designed survey table of the current situation of xerosis and prevention of the elderly, the incidence of xerosis in 1 028 patients hospitalized in Suqian Hospital Affiliated to Xuzhou Medical University, Suqian City Hospital of Traditional Chinese Medicine and Siyang County Hospital of Traditional Chinese Medicine was investigated, and the related factors were analyzed.Results:The incidence of xerofosis was 20.23%(208/1028); the incidence of xerosis was 20.23% (208/1 028), which was mainly found in the lower limbs, with the incidence of 53.37% (111/208), among which the incidence of mild xerosis was the most, with the incidence of 51.44% (107/208). The incidence rate of the elderly patients with xerosis between different age, qualifications, nutritional status, comorbidity, Braden score, drug use, main caregivers, departments, and daily skin care were statistically significant ( χ2 values were 6.91-35.71, all P<0.05). Binary logistic regression analysis showed that age, nutritional status, comorbidity status, Braden score and daily skin care were the independent influencing factors of skin dryness in elderly inpatients. Conclusions:There is a common skin symptom of xerosis in the elderly. It is necessary to establish a standardized management process and take targeted preventive and nursing measures.

BACKGROUND: Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults. METHODS: We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality. RESULTS: Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease. CONCLUSION Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.
Aged ; Arthritis, Rheumatoid ; Asians ; China/epidemiology* ; Humans ; Hypertension ; Middle Aged ; Multimorbidity

Objective:To construct a prognosis associated micro RNA(miRNA) prediction model based on bioinformatics analysis and evaluate its application value in pancreatic cancer patients.Methods:The retrospective cohort study was conducted. The clinicopathological data of 171 pancreatic cancer patients from the Cancer Genome Atlas (TCGA) (https: //cancergenome.nih.gov/) between establishment of database and September 2017 were collected. There were 93 males and 78 females, aged from 35 to 88 years, with a median age of 65 years. Of the 171 patients, 64 had complete clinicopathological data. Patients were allocated into training dataset consisting of 123 patients and validation dataset consisting of 48 patients using the random sampling method, with a ratio of 7∶3. The training dataset was used to construct a prediction model, and the validation dataset was used to evaluate performance of the prediction model. Nine pairs of miRNA sequencing data (GSE41372) of pancreatic cancer and adjacent tissues were downloaded from Gene Expression Omnibus database. The candidate miRNAs were selected from differentially expressed miRNAs in pancreatic cancer and adjacent tissues for LASSO-COX regression analysis based on the patients of training dataset. A prognosis associated miRNA prediction model was constructed upon survival associated miRNAs which were selected from candidate differentially expressed miRNAs. The performance of prognosis associated miRNA prediction model was validated in training dataset and validation dataset, the accuracy of model was evaluated using the area under curve (AUC) of the receiver operating characteristic curves and the efficiency was evaluated using the consistency index (C-index). Observation indicarors: (1) survival of patients; (2) screening results of differentially expressed miRNAs; (3) construction of prognosis associated miRNA model; (4) validation of prognosis associated miRNA model; (5) comparison of clinicopathological factors in pancreatic cancer patients; (6) analysis of factors for prognosis of pancreatic cancer patients; (7) comparison of prediction performance between prognosis associated miRNA model and the eighth edition TNM staging. Measurement data with normal distribution were represented as Mean± SD, comparison between groups was analyzed by the student- t test, and comparison between multiple groups was analyzed by the AVONA. Measurement data with skewed data were represented as M (range), and comparison between groups was analyzed using the Mann-Whitney U test. Count data were described as absolute numbers or percentages, and comparison between groups was conducted using the chi-square test. Ordinal data were analyzed using the rank sum test. Correlation analysis was conducted based on count data to mine the correlation between prognosis associated miRNA model and clinicopathological factors. COX univariate analysis and multivariate analysis were applied to evaluate correlation with the results described as hazard ratio ( HR) and 95% confidence interval ( CI). HR<1 indicated the factor as a protective factor, HR>1 indicated the factor as a risk factor, and HR equal to 1 indicated no influence on survival. The Kaplan-Meier method was used to draw survival curve and calculate survival rates, and the Log-rank test was used for survival analysis. Results:(1) Survival of patients: 123 patients in the training dataset were followed up for 31-2 141 days, with a median follow-up time of 449 days. The 3- and 5-year survival rates were 16.67% and 8.06%. Forty-eight patients in the validation dataset were followed up for 41-2 182 days, with a median follow-up time of 457 days. The 3- and 5-year survival rates were 15.63% and 9.68%. There was no significant difference in the 3- or 5-year survival rates between the two groups ( χ2=0.017, 0.068, P>0.05). (2) Screening results of differentially expressed miRNAs. Results of bioinformatics analysis showed that 102 candidate differentially expressed miRNAs were selected, of which 63 were up-regulated in tumor tissues while 39 were down-regulated. (3) Construction of prognosis associated miRNA model: of the 102 candidate differentially expressed miRNAs, 5 survival associated miRNAs were selected, including miR-21, miR-125a-5p, miR-744, miR-374b, miR-664. The differential expression patterns of pancreatic cancer to adjacent tissues were up-regulation, up-regulation, down-regulation, up-regulation, and down-regulation, respectively, with the fold change of 4.00, 3.43, 3.85, 2.62, and 2.35. A prognostic expression equation constructed based on 5 survival associated miRNAs = 0.454×miR-21 expression level-0.492×miR-125a-5p expression level-0.49×miR-744 expression level-0.419×miR-374b expression level-0.036×miR-664 expression level. (4) Validation of prognosis associated miRNA model: The C-index of prognosis associated miRNA model was 0.643 and 0.642 for the training dataset and validation dataset, respectively. (5) Comparison of clinicopathological factors in pancreatic cancer patients: results of COX analysis showed that the prognosis associated miRNA model was highly related with pathological T stage and location of pancreatic cancer ( Z=45.481, χ2=10.176, P<0.05). (6) Analysis of factors for prognosis of pancreatic cancer patients: results of univariate analysis showed that pathological N stage, radiotherapy, molecular targeted therapy, score of prognosis associated miRNA model were related factors for prognosis pf pancreatic cancer patients ( HR=2.471, 0.290, 0.172, 2.001, 95% CI: 1.012-6.032, 0.101-0.833, 0.082-0.364, 1.371-2.922, P<0.05). Results of multivariate analysis showed that molecular targeted therapy was an independent protective factor for prognosis of pancreatic cancer patients ( HR=0.261, 95% CI: 0.116-0.588, P<0.05) and score of prognosis associated miRNA model≥1.16 was an independent risk factor for prognosis of pancreatic cancer patients ( HR=1.608, 95% CI: 1.091-2.369, P<0.05). (7) Comparison of prediction performance between prognosis associated miRNA model and the eighth edition TNM staging: in the training dataset, there was a significant difference in the prediction probability for 3- and 5-year survival of pancreatic cancer patients between prognosis associated miRNA model and the eighth edition TNM staging ( Z=-1.671, -1.867, P<0.05). The AUC of the prognosis associated miRNA model and the eight edition TNM staging for 3- and 5-year survival prediction was 0.797, 0.935 and 0.737 , 0.703, with the 95% CI of 0.622-0.972, 0.828-1.042 and 0.571-0.904 , 0.456-0.951. The C-index was 0.643 and 0.534. In the validation dataset, there was a significant difference in the prediction probability for 3- and 5-year survival of pancreatic cancer patients between prognosis associated miRNA model and the eighth edition TNM staging ( Z=-1.729, -1.923, P<0.05). The AUC of the prognosis associated miRNA model and the eight edition TNM staging was 0.750, 0.873 and 0.721 , 0.703, with the 95% CI of 0.553-0.948, 0.720-1.025 and 0.553-0.889, 0.456-0.950, respectively. The C-index was 0.642 and 0.544. Conclusions:A prognosis associated miRNA prediction model can be constructed based on 5 survival associated miRNAs in pancreatic cancer patients, as a complementation to current TNM staging and other clinicopathological parameters, which provides individual and accurate prediction of survival for reference in the clinical treatment.