PMID- 34997492 OWN - NLM STAT- MEDLINE DCOM- 20220413 LR - 20220413 IS - 1614-7499 (Electronic) IS - 0944-1344 (Linking) VI - 29 IP - 20 DP - 2022 Apr TI - The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing. PG - 30102-30113 LID - 10.1007/s11356-021-17948-8 [doi] AB - Epidemiological studies have demonstrated that various kinds of urinary element concentrations were different between healthy, prediabetes, and diabetes patients. Meanwhile, many studies have explored the relationship between element concentration and fasting blood glucose (FBG), but the association between joint exposure to co-existing elements and FBG level has not been well understood. The study explored the associations of joint exposure to co-existing urinary elements with FBG level in a cross-sectional design. 275 retired elderly people were recruited from Beijing, China. The questionnaire survey was conducted, and biological samples were collected. The generalized linear model (GLM) and two-phase Bayesian kernel machine regression (BKMR) model were used to perform in-depth association analysis between urinary elements and FBG. The GLM analysis showed that Zn, Sr, and Cd were significantly correlated with the FBG level, under control potential confounding factors. The BKMR analysis demonstrated 8 elements (Zn, Se, Fe, Cr, Ni, Cd, Mn, and Al) had a higher influence on FBG (posterior inclusion probabilities > 0.1). Further intensive analyses result of the BKMR model indicated that the overall estimated exposure of 8 elements was positively correlated with the FBG level and was statistically significant when all creatinine-adjusted element concentrations were at their 65th percentile. Meanwhile, the BKMR analysis showed that Cd and Zn had a statistically significant association with FBG levels when other co-existing elements were controlled at different levels (25th, 50th, or 75th percentile), respectively. The results of the GLM and BKMR model were inconsistent. The BKMR model could flexibly calculate the joint exposure to co-existing elements, evaluate the possible interaction effects and nonlinear correlations. The meaningful conclusions were found that it was difficult to get by traditional methods. This study will provide methodological reference and experimental evidence for the association between joint exposure to co-existing elements and FBG in elderly people. CI - (c) 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. FAU - Liu, Liu AU - Liu L AD - China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. AD - Chaoyang District Center for Disease Control and Prevention, Beijing, China. FAU - Li, Ang AU - Li A AD - Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking, Union Medical College, Beijing, China. AD - Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China. FAU - Xu, Qun AU - Xu Q AD - Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking, Union Medical College, Beijing, China. AD - Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China. FAU - Wang, Qin AU - Wang Q AD - China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. FAU - Han, Feng AU - Han F AD - Chinese Center for Disease Control and Prevention, The National Institute for Occupational Health and Poison Control, Beijing, China. FAU - Xu, Chunyu AU - Xu C AD - China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. FAU - Liu, Zhe AU - Liu Z AD - China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. FAU - Xu, Dongqun AU - Xu D AD - China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. xudq@chinacdc.cn. FAU - Xu, Donggang AU - Xu D AD - Beijing Institute of Basic Medical Sciences, Beijing, China. xudg@bmi.ac.cn. LA - eng GR - 15-230/china medical board/ PT - Journal Article DEP - 20220108 PL - Germany TA - Environ Sci Pollut Res Int JT - Environmental science and pollution research international JID - 9441769 RN - 00BH33GNGH (Cadmium) RN - IY9XDZ35W2 (Glucose) SB - IM MH - Aged MH - Bayes Theorem MH - Beijing MH - *Cadmium MH - Cross-Sectional Studies MH - *Fasting MH - Glucose MH - Humans OTO - NOTNLM OT - Bayesian kernel machine regression OT - Co-existing element,.Fasting blood glucose OT - Diabetes mellitus OT - Urine EDAT- 2022/01/09 06:00 MHDA- 2022/04/14 06:00 CRDT- 2022/01/08 06:12 PHST- 2021/07/07 00:00 [received] PHST- 2021/12/01 00:00 [accepted] PHST- 2022/01/09 06:00 [pubmed] PHST- 2022/04/14 06:00 [medline] PHST- 2022/01/08 06:12 [entrez] AID - 10.1007/s11356-021-17948-8 [pii] AID - 10.1007/s11356-021-17948-8 [doi] PST - ppublish SO - Environ Sci Pollut Res Int. 2022 Apr;29(20):30102-30113. doi: 10.1007/s11356-021-17948-8. Epub 2022 Jan 8.