Objective To assess the exposure levels of heavy metals,including lead,arsenic,mercury,and cadmium,in the local population in Sichuan and Chongqing,China,to compare and analyze the differences in reference intervals(RIs)obtained from direct and indirect sampling methods,and to explore the interchangeability and limitations of these two sampling methods.Methods RIs were obtained by the direct sampling method and the indirect sampling method.In the direct sample method,the levels of blood arsenic,urinary cadmium,urinary mercury,and blood lead levels of 5562 healthy participants aged 22-50 years in Sichuan and Chongqing,China were measured by atomic absorption spectrometry and inductively coupled plasma-mass spectrometry.Using the human biomonitoring(HBM)data,we established RIs for the population by a nonparametric method.On the other hand,in the indirect sampling method,RIs were established via a nonparametric method based on data from the laboratory information system(LIS)of a local hospital after stratifying healthy individuals using a Gaussian mixture model(GMM).Comparative analysis of the RIs derived from the two sampling methods were then conducted.Results The RI for blood arsenic was 0.11-1.3 μmol/L.The RI for urinary cadmium was 0.51-2.80 μmol/mol creatine for adults aged 22 to under 43 years and 0.66-2.96 μmol/mol creatine for adults aged 43-50 years.The RI for urinary mercury was 0.12-1.10 μmol/mol creatine.The RI for blood lead was 14.00-47.00 pg/L for adults aged 22 to under 41 year,16.00-53.38 pg/L for males aged 41-50 year,and 15.00-51.02 pg/L for females aged 41-50 year.Most of the RIs established by the direct sampling method had a narrower range compared to those established by the indirect sampling method,and the RIs established by both sampling methods were partially biased.Conclusions The RIs for blood arsenic,urine cadmium,urine mercury,and blood lead in healthy individuals aged 22-50 years in Sichuan and Chongqing,China were established using both direct and indirect sampling methods,which contributes to a better understanding of environmental exposure to metals in the general population and provides a reference for metal poisoning.For data from the same lab,the GMM-based indirect sampling method demonstrated relatively consistent performance in establishing RIs compared with the direct sampling method.

Objective To establish a universally applicable logistic risk prediction model for diabetes mellitus type 2(T2DM)in the middle-aged and elderly populations based on the results of a Meta-analysis,and to validate and confirm the efficacy of the model using the follow-up data of medical check-ups of National Basic Public Health Service.Methods Cohort studies evaluating T2DM risks were identified in Chinese and English databases.The logistic model utilized Meta-combined effect values such as the odds ratio(OR)to derive β,the partial regression coefficient,of the logistic model.The Meta-combined incidence rate of T2DM was used to obtain the parameter α of the logistic model.Validation of the predictive performance of the model was conducted with the follow-up data of medical checkups of National Basic Public Health Service.The follow-up data came from a community health center in Chengdu and were collected between 2017 and 2022 from 7 602 individuals who did not have T2DM at their baseline medical checkups done at the community health center.This community health center was located in an urban-rural fringe area with a large population of middle-aged and elderly people.Results A total of 40 cohort studies were included and 10 items covered in the medical checkups of National Basic Public Health Service were identified in the Meta-analysis as statistically significant risk factors for T2DM,including age,central obesity,smoking,physical inactivity,impaired fasting glucose,a reduced level of high-density lipoprotein cholesterol(HDL-C),hypertension,body mass index(BMI),triglyceride glucose(TYG)index,and a family history of diabetes,with the OR values and 95% confidence interval(CI)being 1.04(1.03,1.05),1.55(1.29,1.88),1.36(1.11,1.66),1.26(1.07,1.49),3.93(2.94,5.24),1.14(1.06,1.23),1.47(1.34,1.61),1.11(1.05,1.18),2.15(1.75,2.62),and 1.66(1.55,1.78),respectively,and the combined β values being 0.039,0.438,0.307,0.231,1.369,0.131,0.385,0.104,0.765,and 0.507,respectively.A total of 37 studies reported the incidence rate,with the combined incidence being 0.08(0.07,0.09)and the parameter α being-2.442 for the logistic model.The logistic risk prediction model constructed based on Meta-analysis was externally validated with the data of 7 602 individuals who had medical checkups and were followed up for at least once.External validation results showed that the predictive model had an area under curve(AUC)of 0.794(0.771,0.816),accuracy of 74.5%,sensitivity of 71.0%,and specificity of 74.7% in the 7 602 individuals.Conclusion The T2DM risk prediction model based on Meta-analysis has good predictive performance and can be used as a practical tool for T2DM risk prediction in middle-aged and elderly populations.