Objective Previous studies on the association between lipid profiles and chronic kidney disease(CKD)have yielded inconsistent results and no defined thresholds for blood lipids. Methods A prospective cohort study including 32,351 subjects who completed baseline and follow-up surveys over 5 years was conducted.Restricted cubic splines and Cox models were used to examine the association between the lipid profiles and CKD.A regression discontinuity design was used to determine the cutoff value of lipid profiles that was significantly associated with increased the risk of CKD. Results Over a median follow-up time of 2.2(0.5,4.2)years,648(2.00%)subjects developed CKD.The lipid profiles that were significantly and linearly related to CKD included total cholesterol(TC),triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),TC/HDL-C,and TG/HDL-C,whereas low-density lipoprotein cholesterol(LDL-C)and LDL-C/HDL-C were nonlinearly correlated with CKD.TC,TG,TC/HDL-C,and TG/HDL-C showed an upward jump at the cutoff value,increasing the risk of CKD by 0.90%,1.50%,2.30%,and 1.60%,respectively,whereas HDL-C showed a downward jump at the cutoff value,reducing this risk by 1.0%.Female and participants with dyslipidemia had a higher risk of CKD,while the cutoff values for the different characteristics of the population were different. Conclusion There was a significant association between lipid profiles and CKD in a prospective cohort from Northwest China,while TG,TC/HDL-C,and TG/HDL-C showed a stronger risk association.The specific cutoff values of lipid profiles may provide a clinical reference for screening or diagnosing CKD risk.

Background Current evidence on whether occupational sulfur dioxide (SO₂) exposure affects the risk of hypertension is still limited, and the research results of the effect of environmental SO₂ exposure on risk of hypertension remain inconsistent. Objective To analyze the association between self-reported occupational exposure to SO₂ and the risk of hypertension, and the potential dose-response relationship between the years of exposure to SO₂ and the risk of hypertension. Methods Based on the Jinchang cohort, a nested case-control study design was adopted. A total of 841 newly diagnosed hypertension patients were followed up as the case group, and the control group was selected with 1∶1 individual matching based on non-occupational factors and occupational factors, respectively. The former matching conditions included age ±2 years old, same gender, working age ±2 years, and home address in the same sub-district. The latter was limited to working in the same workshop on the basis of the former conditions. Finally, the former included 717 controls and the latter included 488 controls. A unified questionnaire was used to collect general demographic characteristics, lifestyle habits, history of diabetes, family history of hypertension, and information on occupational exposure to SO₂ (self-reported history of occupational exposure to SO₂ and years of exposure to SO₂). Conditional logistic regression model was used to analyze the association between occupational exposure to SO₂ and hypertension, and the dose-response relationship between the years of SO₂ exposure and the risk of hypertension. Results In the nested case-control study matching with the non-occupational factors, the OR of hypertension in workers with self-reported occupational exposure to SO₂ was 2.39 (95%CI: 1.68-3.39); while when matching with the occupational factors, the OR of hypertension in workers with self-reported occupational exposure to SO₂ was 1.48 (95%CI: 1.04-2.12). The results of the dose-response relationship showed that as the SO₂ exposure years increased from 1-9 years, 10-19 years, 20-29 years, and 30 years and above, in the nested case-control study matching with non-occupational factors, the ORs of hypertension were 1.85 (95%CI: 0.68-5.08), 1.46 (95%CI: 0.58-3.67), 1.64 (95%CI: 1.00-2.67), and 4.95 (95%CI: 2.63-9.31), respectively; in the nested case-control study matching with occupational factors, the ORs of hypertension were 0.98 (95%CI: 0.40-2.41), 1.84 (95%CI: 0.72-4.70), 1.37 (95%CI: 0.82-2.29), and 2.44 (95%CI: 1.37-4.35), respectively. The two dose-response relationships were positive by χ² trend test (P_trend<0.05). Conclusion Self-reported occupational exposure to SO₂ is associated with the risk of hypertension in the study population, and the hypertension risk increases with the increase of SO₂ exposure years.

Objective:To investigate the relationship of triglyceride (TG), fasting blood glucose (FPG) and triglyceride glucose product index (TyG) with the incidence of hypertension, and provide basic data for the prevention and treatment of hypertension in the population.Methods:A total of 23 581 individuals who met the research criteria in Jinchang cohort were selected as the research subjects, the Cox proportional hazard model was used to analyze the relationship of TG, FPG, and TyG with the risk of hypertension. A stratified analysis was conducted by sex.Results:After adjusting for confounding factors, compared with the normal TG group, the HR(95% CI) of the elevated TG margin group and the elevated group were 1.16 (1.01-1.34) and 1.49 (1.30-1.70), respectively in the total population. Among men, they were 1.13 (1.01-1.27) and 1.17 (1.06-1.30), and among women, they were 1.05 (0.88-1.26) and 1.06 (0.88-1.28). Compared with the normal FPG group, the HR (95% CI) of the FPG-impaired group were 1.29 (1.13-1.48) in the total population, 1.26 (1.08-1.48) in men and 1.59 (1.14-2.21) in women. Taking the lowest quartile array as a reference, the HR (95% CI) of the highest quartile array of TyG was 1.73 (1.45-2.07) in the total population, 1.32 (1.14-1.53) in men and 1.87 (1.37-2.54) in women. TG, FPG had a nonlinear dose-response relationship with the risk of hypertension, while TyG had a linear correlation with the risk of hypertension. Conclusions:Higher TG, FPG, and TyG levels are independent risk factors for the incidence of hypertension. People with higher TG, FPG and TyG are at high risk for hypertension, to which close attention should be paid in the prevention and treatment of hypertension.

Objective:To investigate the influence of HBV infection on the prevalence of fatty liver disease in Jinchang cohort and provide theoretical evidence for the prevention and treatment of fatty liver disease.Methods:Epidemiological investigation, laboratory examination and abdominal ultrasound were conducted in the baseline population of Jinchang cohort to collect the basic data, the differences in the prevalence of fatty liver disease under different HBV infection patterns were described and compared and the influence of different HBV infection patterns on the prevalence of fatty liver disease were evaluated by using logistic regression analysis.Results:The baseline Jinchang cohort population totaled 45 605, including 27 917 males and 17 688 females. The male to female ratio was 1.6∶1. The mean age of the overall population was 46.49 years. Among the 8 common HBV infection modes in the Jinchang cohort, the prevalence of fatty liver was low in HBsAg, HBeAg and HBcAb positive, HBsAg and HBcAb positive, and HBsAg, HBeAb and HBcAb positive groups. For 4 serum markers of HBV infection, the prevalence of fatty liver disease in HBsAg and HBeAg positive groups was lower than that in HBsAg and HBeAg negative groups. Logistic regression analysis showed that being HBsAg and HBcAb positive ( OR=0.61, 95% CI: 0.39-0.98) and HBsAg, HBeAg and HBcAb positive ( OR=0.52, 95% CI: 0.30-0.89) could reduce the risk for fatty liver disease. Conclusion:Acute HBV infection reduces the prevalence of fatty liver disease, and the reason may be related to the disturbance of the body's fat metabolism by active HBV replication.

Objective:To explore the influencing factors for non-alcoholic fatty liver disease (NAFLD) in Jinchang cohort, and provide scientific basis for the prevention and control of NAFLD.Methods:A total of 20 051 patients without fatty liver at baseline survey and met the inclusion criteria in Jinchang cohort were selected as study subjects. Prospective cohort study and Cox regression analysis were used to investigate the influencing factors for NAFLD, and the dose-response relationship between related biochemical indicators and NAFLD risk was studied by restricted cubic spline method.Results:The incidence of NAFLD was 42.37/1 000 person years. Multivariate Cox regression analysis showed that being worker and technical personnel (being worker: HR=0.84,95% CI:0.70-0.99;being technical personnel: HR=0.73,95% CI:0.56-0.95), tea drinking (current drinking: HR=0.86,95% CI:0.78-0.94;previous drinking: HR=0.52,95% CI: 0.31-0.86), exercise (occasionally: HR=0.79, 95% CI: 0.68-0.91;frequently: HR=0.60,95% CI:0.52-0.69), low body weight ( HR=0.10, 95% CI: 0.05-0.22), daily intake of dairy products >300 ml/day ( HR=0.78, 95% CI: 0.71-0.87) and HBV infection ( HR=0.77, 95% CI: 0.60-0.99) were the protective factors for NAFLD, while being internal or office workers ( HR=1.84, 95% CI: 1.46-2.31), income ≥2 000 yuan (2 000- yuan: HR=1.32, 95% CI: 1.04-1.66; ≥5 000 yuan: HR=1.72, 95% CI:1.11-2.66), bachelor degree or above ( HR=1.35,95% CI:1.03-1.76), overweight ( HR=2.31, 95% CI:2.08-2.55), obesity ( HR=3.95, 95% CI: 3.42-4.56), impaired fasting blood glucose ( HR=1.31, 95% CI:1.17-1.47), diabetes ( HR=1.53, 95% CI: 1.30-1.80), increased TC ( HR=1.37,95% CI:1.24-1.52), increased TG ( HR=1.79,95% CI: 1.62-1.98), decreased HDL-C ( HR=1.29, 95% CI: 1.14-1.45), increased ALT ( HR=1.13, 95% CI: 1.01-1.26) and high-fat diet ( HR=1.24, 95% CI: 1.11-1.40) were the risk factors for NAFLD. Moreover, TC, TG, HDL-C, ALT and FPG all showed good dose-response relationship with the incidence of NAFLD. Conclusion:Occupation, education level, income level, tea drinking, exercise, BMI, FPG, blood lipid, ALT, HBV infection and diet were related to the incidence of NAFLD.

Objective:To explore the relationship between lipid indicators and the incidence of diabetes, and to compare the diabetes prediction and identification power of traditional lipid combined lipid indicators, in order to explore the best alternative indicators for identifying and predicting diabetes.Methods:Based on the Jinchang cohort, a nested case-control study was conducted in 1 025 new cases of diabetes after excluding patients with malignant tumor and related endocrine, circulatory system disease, then an age (±2 years), gender matched 1∶1 control group of 1 025 cases was set to analyze the relationship between the incidence of diabetes and lipid parameters.Results:Among the traditional lipid parameters, the fourth quartile of TG, TC, and LDL-C indicated higher risks of developing diabetes, which was 14.00 times (95% CI: 9.73-20.15), 2.15 times (95% CI: 1.65-2.79) and 1.66 times (95% CI: 1.29-2.14) than that of the first quartile, respectively. The risk of developing diabetes indicated by the fourth quartile of HDL-C was 0.21 times than that indicated by the first quartile (95% CI: 0.15-0.28). In the combined lipid parameters, the fourth quartile of TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C indicated higher risks of developing diabetes, which was 14.86 times (95% CI: 10.35-21.34), 8.12 times (95% CI: 5.94-11.01), 5.85 times (95% CI:4.34-7.88) and 5.20 times (95% CI: 3.85-7.03) than that indicated by the first quartile, respectively. The areas under the ROC curve of TG, TC, HDL-C, LDL-C, TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C were 0.76 (95% CI: 0.74-0.78), 0.59 (95% CI: 0.57-0.61), 0.67 (95% CI: 0.65-0.69), 0.57 (95% CI: 0.55-0.59), 0.77 (95% CI: 0.75-0.78), 0.73 (95% CI: 0.71-0.75), 0.69 (95% CI: 0.67-0.71) and 0.66 (95% CI: 0.64-0.68), respectively. The optimal diabetes predicting point cuts of TG, TC, HDL-C, LDL-C, TG/HDL-C, TC/HDL-C, LDL-C/HDL-C and non-HDL-C were 1.40, 4.70, 1.28, 3.25, 1.17, 3.43, 2.46, and 3.58 mmol/L, respectively. Conclusions:Lipid metabolic disorder is a risk factor for diabetes. TG and TG/HDL-C are the good lipid metabolism indicators for the prediction of diabetic.

Objective:To explore the relationship of body mass index and blood pressure with the incidence of diabetes in Jinchang cohort.Methods:We designed a nested case-control study, a total of 29 572 workers who had no history of diabetes in baseline survey in Jinchang cohort were selected as the study cohort from June 2011 to December 2013. After 2 year follow-up, 1 021 workers with first diagnosed diabetes were selected as the case group, after 1∶1 matching according to the same gender and age ±2 years among those without diabetes, circulatory system, or endocrine system diseases during the same follow-up period, 1 021 controls was selected and 2 042 subjects were finally included. We used multivariate conditional logistic regression model, additive interaction model and multiplicative interaction model to explore the relationship of body mass index and blood pressure with the incidence of diabetes.Results:After adjusting for factors such as occupation, alcohol use, family history of diabetes, hyperuricemia, hypercholesterolemia, hypertriglyceridemia, low-HDL cholesterolemia and high-LDL cholesterolemia, multivariate conditional logistic regression analysis showed that the risk of diabetes increased with body mass index and blood pressure. Hypertension and overweight/obesity had a multiplicative interaction on the incidence of diabetes. The risks of diabetes in men and women with hypertension and overweight/obese were 2.04 times (95% CI: 1.54-2.69) and 3.88 times (95% CI: 2.55-5.91) higher than those in men and women with normal body weight and blood pressure, respectively. In the combination of BMI and blood pressure, obese individuals with SBP≥160 mmHg were 4.57 times (95% CI: 2.50-8.34) more likely to have diabetes than those with normal BMI and SBP, obese individuals with DBP≥90 mmHg were 3.40 times (95% CI: 2.19-5.28) more likely to have diabetes than those with normal BMI and DBP. Conclusions:Overweight/obesity and hypertension can increase the risk of diabetes. Health education about body weight and blood pressure controls should be strengthened to reduce the risk of diabetes.

Objective:To explore the effect of long-term exposure to ambient particulate matter (PM 10) on the prevalence of diabetes and fasting plasma glucose (FPG). Methods:The subjects of the study were from the baseline population of "Jinchang Cohort", and 24 285 subjects were finally included after excluding incomplete home address information and diabetic diagnosis information. The demographic characteristics, lifestyle and health status of the survey subjects were collected through questionnaire, physical examination and laboratory tests. ArcGIS software was used to match the nearest environmental monitoring stations for each subject according to residential address. Two-year average concentrations of PM 10 were calculated to estimate exposure level. The logistic regression and the multiple linear regression were conducted to assess the effects of ambient PM 10 on the prevalence of diabetes and FPG. The restricted cubic spline was used to quantify the dose-response relationship. Stratified analysis and effect modification analysis were also performed. Results:The age of 24 285 participants was (49.32±8.60) years, and the BMI was (24.22±6.09) kg/m 2. There were 13 950 (57.44%) males and 2 066 (8.51%) diabetic patients. After adjusting for confounders, for every 10 μg/m 3 increase in the average PM 10 concentration in the first two years of the survey, the prevalence of diabetes increased [ OR (95% CI) =1.05 (1.01-1.09)]and the FPG level elevated [β (95% CI) = 0.061 (0.047-0.076) mmol/L]. The results of the restricted cubic spline analysis showed a nonlinear relationship between PM 10 concentration and FPG level ( P<0.001). Further subgroup analysis showed that female [ OR (95% CI) =1.10 (1.03-1.18)], people over 50 years old [ OR (95% CI) =1.06 (1.02-1.11) ], subjects with family history of diabetes [ OR (95% CI) = 1.13 (1.04-1.23) ], and with hypertension [ OR (95% CI) = 1.07 (1.02-1.12) ] had a stronger association between the prevalence of diabetes and PM 10 exposure (all P interaction values were<0.05). The effects of PM 10 on FPG were more significant in people older than 50 years[β (95% CI) = 0.080 (0.050-0.109) mmol/L], with family history of diabetes [β (95% CI) = 0.087 (0.036-0.137) mmol/L], and hypertension [β (95% CI) = 0.077 (0.046-0.108) mmol/L] (all P interaction values were<0.05). Conclusions:Long-term exposure to ambient PM 10 increases the diabetes prevalence and FPG. People older than 50 years old, with family history of diabetes and hypertension could be more sensitive to the effects of PM 10 exposure.

Objective:To explore the effect of long-term exposure to ambient particulate matter (PM 10) on the prevalence of diabetes and fasting plasma glucose (FPG). Methods:The subjects of the study were from the baseline population of "Jinchang Cohort", and 24 285 subjects were finally included after excluding incomplete home address information and diabetic diagnosis information. The demographic characteristics, lifestyle and health status of the survey subjects were collected through questionnaire, physical examination and laboratory tests. ArcGIS software was used to match the nearest environmental monitoring stations for each subject according to residential address. Two-year average concentrations of PM 10 were calculated to estimate exposure level. The logistic regression and the multiple linear regression were conducted to assess the effects of ambient PM 10 on the prevalence of diabetes and FPG. The restricted cubic spline was used to quantify the dose-response relationship. Stratified analysis and effect modification analysis were also performed. Results:The age of 24 285 participants was (49.32±8.60) years, and the BMI was (24.22±6.09) kg/m 2. There were 13 950 (57.44%) males and 2 066 (8.51%) diabetic patients. After adjusting for confounders, for every 10 μg/m 3 increase in the average PM 10 concentration in the first two years of the survey, the prevalence of diabetes increased [ OR (95% CI) =1.05 (1.01-1.09)]and the FPG level elevated [β (95% CI) = 0.061 (0.047-0.076) mmol/L]. The results of the restricted cubic spline analysis showed a nonlinear relationship between PM 10 concentration and FPG level ( P<0.001). Further subgroup analysis showed that female [ OR (95% CI) =1.10 (1.03-1.18)], people over 50 years old [ OR (95% CI) =1.06 (1.02-1.11) ], subjects with family history of diabetes [ OR (95% CI) = 1.13 (1.04-1.23) ], and with hypertension [ OR (95% CI) = 1.07 (1.02-1.12) ] had a stronger association between the prevalence of diabetes and PM 10 exposure (all P interaction values were<0.05). The effects of PM 10 on FPG were more significant in people older than 50 years[β (95% CI) = 0.080 (0.050-0.109) mmol/L], with family history of diabetes [β (95% CI) = 0.087 (0.036-0.137) mmol/L], and hypertension [β (95% CI) = 0.077 (0.046-0.108) mmol/L] (all P interaction values were<0.05). Conclusions:Long-term exposure to ambient PM 10 increases the diabetes prevalence and FPG. People older than 50 years old, with family history of diabetes and hypertension could be more sensitive to the effects of PM 10 exposure.

Objective: To understand the health literacy and relevant factors of cancer prevention consciousness in Chinese urban residents from 2015 to 2017. Methods: A cross-sectional survey was conducted in 16 provinces covered by the Cancer Screening Program in Urban China from 2015 to 2017. A total of 32 257 local residents aged ≥18 years old who could understand the investigation procedure were included in the study by using the cluster sampling method and convenient sampling method. All local residents were categorized into four groups, which contained 15 524 community residents, 8 016 cancer risk assessment/screening population, 2 289 cancer patients and 6 428 occupational population, respectively. The self-designed questionnaire was used to collect the information of demographic characteristics and cancer prevention consciousness focusing on nine common risk factors, including smoking, alcohol, fiber food, food in hot temperature or pickled food, chewing betel nut, helicobacter pylori, moldy food, hepatitis B infection, estrogen, and exercise. The logistic regression model was adopted to identify the influencing factors. Results: The overall health literacy of the cancer prevention consciousness was 77.4% (24 980 participants), with 77.4% (12 018 participants), 79.9% (6 406 participants), 77.2% (1 766 participants) and 74.5% (4 709 participants) in each group (P<0.001). The correct response rates for nine risk factors ranged from 55.2% to 93.0%. The multivariate logistic regression analysis showed that compared with community residents, people with primary school level education or below, and the number of people living together in the family <3, the cancer risk assessment/screening intervention population, cancer patients, those with junior high school level educationor above and the number of people living in the family ≥3 had better health literacy of the cancer prevention consciousness (all P values <0.05). Compared with females, 39 years old and below, government-affiliated institutions or civil servants, from the eastern region, males, older than 40 years, company or enterprise employees, and from the middle or western region had worse health literacy of the cancer prevention consciousness (all P values <0.05). Conclusion The health literacy of the cancer prevention consciousness in Chinese urban residents should be improved. The cancer screening intervention, gender, age, education, occupation, the number of people co-living in the family, and residential region were associated with the health literacy of the cancer prevention consciousness.