Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study
Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Xiaoyi [verfasserIn] Gao, Duan [verfasserIn] Zhang, Guofu [verfasserIn] Zhang, Xu [verfasserIn] Li, Qian [verfasserIn] Gao, Qin [verfasserIn] Chen, Renjuan [verfasserIn] Xu, Shangzhi [verfasserIn] Huang, Li [verfasserIn] Zhang, Yu [verfasserIn] Lin, Lixia [verfasserIn] Zhong, Chunrong [verfasserIn] Chen, Xi [verfasserIn] Sun, Guoqiang [verfasserIn] Song, Yang [verfasserIn] Yang, Xuefeng [verfasserIn] Hao, Liping [verfasserIn] Yang, Hongying [verfasserIn] Yang, Lei [verfasserIn] Yang, Nianhong [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Environment international - Amsterdam [u.a.] : Elsevier Science, 1978, 135 |
|---|---|
| Übergeordnetes Werk: |
volume:135 |
| DOI / URN: |
10.1016/j.envint.2019.105370 |
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| Katalog-ID: |
ELV003438872 |
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| 245 | 1 | 0 | |a Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study |
| 264 | 1 | |c 2019 | |
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| 520 | |a Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. | ||
| 650 | 4 | |a GDM | |
| 650 | 4 | |a Urinary metals | |
| 650 | 4 | |a Single-metal models | |
| 650 | 4 | |a Multiple-metal models | |
| 650 | 4 | |a BKMR models | |
| 700 | 1 | |a Gao, Duan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Guofu |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Xu |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Qian |e verfasserin |4 aut | |
| 700 | 1 | |a Gao, Qin |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Renjuan |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Shangzhi |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Li |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yu |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Lixia |e verfasserin |4 aut | |
| 700 | 1 | |a Zhong, Chunrong |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Xi |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Guoqiang |e verfasserin |4 aut | |
| 700 | 1 | |a Song, Yang |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Xuefeng |e verfasserin |4 aut | |
| 700 | 1 | |a Hao, Liping |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Hongying |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Lei |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Nianhong |e verfasserin |4 aut | |
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2019 |
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2019 |
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10.1016/j.envint.2019.105370 doi (DE-627)ELV003438872 (ELSEVIER)S0160-4120(19)32397-9 DE-627 ger DE-627 rda eng 690 610 600 DE-600 30.00 bkl 44.13 bkl Wang, Xiaoyi verfasserin aut Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. GDM Urinary metals Single-metal models Multiple-metal models BKMR models Gao, Duan verfasserin aut Zhang, Guofu verfasserin aut Zhang, Xu verfasserin aut Li, Qian verfasserin aut Gao, Qin verfasserin aut Chen, Renjuan verfasserin aut Xu, Shangzhi verfasserin aut Huang, Li verfasserin aut Zhang, Yu verfasserin aut Lin, Lixia verfasserin aut Zhong, Chunrong verfasserin aut Chen, Xi verfasserin aut Sun, Guoqiang verfasserin aut Song, Yang verfasserin aut Yang, Xuefeng verfasserin aut Hao, Liping verfasserin aut Yang, Hongying verfasserin aut Yang, Lei verfasserin aut Yang, Nianhong verfasserin aut Enthalten in Environment international Amsterdam [u.a.] : Elsevier Science, 1978 135 Online-Ressource (DE-627)306580829 (DE-600)1497569-5 (DE-576)096188626 1873-6750 nnns volume:135 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 30.00 Naturwissenschaften allgemein: Allgemeines 44.13 Medizinische Ökologie AR 135 |
| spelling |
10.1016/j.envint.2019.105370 doi (DE-627)ELV003438872 (ELSEVIER)S0160-4120(19)32397-9 DE-627 ger DE-627 rda eng 690 610 600 DE-600 30.00 bkl 44.13 bkl Wang, Xiaoyi verfasserin aut Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. GDM Urinary metals Single-metal models Multiple-metal models BKMR models Gao, Duan verfasserin aut Zhang, Guofu verfasserin aut Zhang, Xu verfasserin aut Li, Qian verfasserin aut Gao, Qin verfasserin aut Chen, Renjuan verfasserin aut Xu, Shangzhi verfasserin aut Huang, Li verfasserin aut Zhang, Yu verfasserin aut Lin, Lixia verfasserin aut Zhong, Chunrong verfasserin aut Chen, Xi verfasserin aut Sun, Guoqiang verfasserin aut Song, Yang verfasserin aut Yang, Xuefeng verfasserin aut Hao, Liping verfasserin aut Yang, Hongying verfasserin aut Yang, Lei verfasserin aut Yang, Nianhong verfasserin aut Enthalten in Environment international Amsterdam [u.a.] : Elsevier Science, 1978 135 Online-Ressource (DE-627)306580829 (DE-600)1497569-5 (DE-576)096188626 1873-6750 nnns volume:135 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 30.00 Naturwissenschaften allgemein: Allgemeines 44.13 Medizinische Ökologie AR 135 |
| allfields_unstemmed |
10.1016/j.envint.2019.105370 doi (DE-627)ELV003438872 (ELSEVIER)S0160-4120(19)32397-9 DE-627 ger DE-627 rda eng 690 610 600 DE-600 30.00 bkl 44.13 bkl Wang, Xiaoyi verfasserin aut Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. GDM Urinary metals Single-metal models Multiple-metal models BKMR models Gao, Duan verfasserin aut Zhang, Guofu verfasserin aut Zhang, Xu verfasserin aut Li, Qian verfasserin aut Gao, Qin verfasserin aut Chen, Renjuan verfasserin aut Xu, Shangzhi verfasserin aut Huang, Li verfasserin aut Zhang, Yu verfasserin aut Lin, Lixia verfasserin aut Zhong, Chunrong verfasserin aut Chen, Xi verfasserin aut Sun, Guoqiang verfasserin aut Song, Yang verfasserin aut Yang, Xuefeng verfasserin aut Hao, Liping verfasserin aut Yang, Hongying verfasserin aut Yang, Lei verfasserin aut Yang, Nianhong verfasserin aut Enthalten in Environment international Amsterdam [u.a.] : Elsevier Science, 1978 135 Online-Ressource (DE-627)306580829 (DE-600)1497569-5 (DE-576)096188626 1873-6750 nnns volume:135 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 30.00 Naturwissenschaften allgemein: Allgemeines 44.13 Medizinische Ökologie AR 135 |
| allfieldsGer |
10.1016/j.envint.2019.105370 doi (DE-627)ELV003438872 (ELSEVIER)S0160-4120(19)32397-9 DE-627 ger DE-627 rda eng 690 610 600 DE-600 30.00 bkl 44.13 bkl Wang, Xiaoyi verfasserin aut Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. GDM Urinary metals Single-metal models Multiple-metal models BKMR models Gao, Duan verfasserin aut Zhang, Guofu verfasserin aut Zhang, Xu verfasserin aut Li, Qian verfasserin aut Gao, Qin verfasserin aut Chen, Renjuan verfasserin aut Xu, Shangzhi verfasserin aut Huang, Li verfasserin aut Zhang, Yu verfasserin aut Lin, Lixia verfasserin aut Zhong, Chunrong verfasserin aut Chen, Xi verfasserin aut Sun, Guoqiang verfasserin aut Song, Yang verfasserin aut Yang, Xuefeng verfasserin aut Hao, Liping verfasserin aut Yang, Hongying verfasserin aut Yang, Lei verfasserin aut Yang, Nianhong verfasserin aut Enthalten in Environment international Amsterdam [u.a.] : Elsevier Science, 1978 135 Online-Ressource (DE-627)306580829 (DE-600)1497569-5 (DE-576)096188626 1873-6750 nnns volume:135 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 30.00 Naturwissenschaften allgemein: Allgemeines 44.13 Medizinische Ökologie AR 135 |
| allfieldsSound |
10.1016/j.envint.2019.105370 doi (DE-627)ELV003438872 (ELSEVIER)S0160-4120(19)32397-9 DE-627 ger DE-627 rda eng 690 610 600 DE-600 30.00 bkl 44.13 bkl Wang, Xiaoyi verfasserin aut Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. GDM Urinary metals Single-metal models Multiple-metal models BKMR models Gao, Duan verfasserin aut Zhang, Guofu verfasserin aut Zhang, Xu verfasserin aut Li, Qian verfasserin aut Gao, Qin verfasserin aut Chen, Renjuan verfasserin aut Xu, Shangzhi verfasserin aut Huang, Li verfasserin aut Zhang, Yu verfasserin aut Lin, Lixia verfasserin aut Zhong, Chunrong verfasserin aut Chen, Xi verfasserin aut Sun, Guoqiang verfasserin aut Song, Yang verfasserin aut Yang, Xuefeng verfasserin aut Hao, Liping verfasserin aut Yang, Hongying verfasserin aut Yang, Lei verfasserin aut Yang, Nianhong verfasserin aut Enthalten in Environment international Amsterdam [u.a.] : Elsevier Science, 1978 135 Online-Ressource (DE-627)306580829 (DE-600)1497569-5 (DE-576)096188626 1873-6750 nnns volume:135 GBV_USEFLAG_U SYSFLAG_U GBV_ELV SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_165 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2008 GBV_ILN_2014 GBV_ILN_2025 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 30.00 Naturwissenschaften allgemein: Allgemeines 44.13 Medizinische Ökologie AR 135 |
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Enthalten in Environment international 135 volume:135 |
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Enthalten in Environment international 135 volume:135 |
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GDM Urinary metals Single-metal models Multiple-metal models BKMR models |
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Environment international |
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Wang, Xiaoyi @@aut@@ Gao, Duan @@aut@@ Zhang, Guofu @@aut@@ Zhang, Xu @@aut@@ Li, Qian @@aut@@ Gao, Qin @@aut@@ Chen, Renjuan @@aut@@ Xu, Shangzhi @@aut@@ Huang, Li @@aut@@ Zhang, Yu @@aut@@ Lin, Lixia @@aut@@ Zhong, Chunrong @@aut@@ Chen, Xi @@aut@@ Sun, Guoqiang @@aut@@ Song, Yang @@aut@@ Yang, Xuefeng @@aut@@ Hao, Liping @@aut@@ Yang, Hongying @@aut@@ Yang, Lei @@aut@@ Yang, Nianhong @@aut@@ |
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2019-01-01T00:00:00Z |
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3690 |
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ELV003438872 |
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englisch |
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However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. 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The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. 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Wang, Xiaoyi Gao, Duan Zhang, Guofu Zhang, Xu Li, Qian Gao, Qin Chen, Renjuan Xu, Shangzhi Huang, Li Zhang, Yu Lin, Lixia Zhong, Chunrong Chen, Xi Sun, Guoqiang Song, Yang Yang, Xuefeng Hao, Liping Yang, Hongying Yang, Lei Yang, Nianhong |
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exposure to multiple metals in early pregnancy and gestational diabetes mellitus: a prospective cohort study |
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Exposure to multiple metals in early pregnancy and gestational diabetes mellitus: A prospective cohort study |
| abstract |
Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. |
| abstractGer |
Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. |
| abstract_unstemmed |
Background: A growing number of epidemiologic studies have estimated associations between type 2 diabetes mellitus and exposure to metals. However, studies on the associations of internal assessments of metal exposure and gestational diabetes mellitus (GDM) are limited in scope and have inconsistent outcomes.Objectives: This investigation aimed to explore the associations between urinary nickel (Ni), arsenic (As), cadmium (Cd), antimony (Sb), cobalt (Co), or vanadium (V) in early pregnancy and the subsequent risk of GDM in Chinese pregnant women.Methods: The study population included 2090 women with singleton pregnancy from the Tongji Maternal and Child Health Cohort (TMCHC). Urine samples were collected before 20 gestational weeks, and an oral glucose tolerance test (OGTT) was conducted at 24–28 gestational weeks to diagnose GDM. The concentrations of urinary metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) and were corrected for urinary creatinine. The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. All six metals mixed exposure was positively associated with the risk of GDM, while Sb and Ni were demonstrated more important effects than the other four metals in the mixture. |
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The associations between the risk of GDM and urinary metals were assessed using Poisson regression with a robust error variance with generalized estimating equations (GEE) models and Bayesian kernel machine regression (BKMR).Results: A total of 241 participants (11.53%) were diagnosed with GDM. Five metals (Ni, As, Sb, Co, and V) were found significantly and positively associated with GDM based on single-metal models. In multiple-metal models, for each unit increase of ln-transformed urinary Ni or Sb, the risk of GDM increased 18% [relative risk (RR):1.18, 95%confidence interval (CI): 1.00, 1.38 or RR: 1.18, 95%CI: 1.00, 1.39, respectively]. The BKMR analysis revealed a statistically significant and positive joint effect of the six metals on the risk of GDM, when the urinary levels of the six metals were all above the 55th percentile, compared to the median levels. The effect of metal Ni was significant when the concentrations of the other metals were all fixed at their 25th percentile, and metal Sb displayed a significant and positive effect when all the other metals were fixed at 25th, 50th, and 75th percentiles.Conclusions: To the best of our knowledge, this study is the first to demonstrate that increased concentrations of urinary Ni in early pregnancy are associated with an elevated risk of GDM, either evaluated individually or as a metal mixture. 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