Association of blood mercury exposure with depressive symptoms in the Chinese oldest old
Depressive symptoms have a significant impact on the quality-of-life among the oldest old (aged ≥ 80 years) in the population. Current research on the association of blood mercury with depressive symptoms has mainly targeted the general population. However, it is unclear whether this association is...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Ecotoxicology and Environmental Safety |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651322008168 |
| _version_ | 1811297329106386944 |
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| author | Jiahui Xiong Yuebin Lv Yuan Wei Zuyun Liu Xinwei Li Jinhui Zhou Yang Liu Feng Zhao Chen Chen Heng Gu Jun Wang Xulin Zheng Kai Xue Yidan Qiu Tong Shen Xiaoming Shi |
| author_facet | Jiahui Xiong Yuebin Lv Yuan Wei Zuyun Liu Xinwei Li Jinhui Zhou Yang Liu Feng Zhao Chen Chen Heng Gu Jun Wang Xulin Zheng Kai Xue Yidan Qiu Tong Shen Xiaoming Shi |
| author_sort | Jiahui Xiong |
| collection | DOAJ |
| description | Depressive symptoms have a significant impact on the quality-of-life among the oldest old (aged ≥ 80 years) in the population. Current research on the association of blood mercury with depressive symptoms has mainly targeted the general population. However, it is unclear whether this association is present in the oldest old. We used data from the Healthy Aging and Biomarker Cohort Study carried out in 2017–2018, with 1154 participants aged ≥ 80 years eligible for analysis. Inductively coupled plasma mass spectrometry (ICP-MS) was employed to detect blood mercury (Hg) levels, while the CES-D10 depression scale was used to assess depressive symptoms. The association between blood mercury levels and depressive symptoms was investigated using log-binomial and Poisson regression models. We also used restricted cubic splines (RCS) to assess the linear or nonlinear association of blood mercury with depressive symptoms scores. The 1154 participants ranged in age from 80 to 120 years, while the geometric mean of blood mercury concentration was 1.01 μg/L. After adjustment for covariates, log-binomial and Poisson regression analyses revealed a statistically significant, positive association of blood mercury with depressive symptoms. In comparison to the first tertile, the adjusted relative risks of blood mercury and the presence of depressive symptoms in the second and third tertiles were 1.55 (1.20–1.99) and 1.45 (1.11–1.90), respectively. The RCS model showed a linear association between blood mercury level and depressive symptoms scores. In conclusion, among the oldest old, we demonstrated that blood mercury levels were positively associated with depressive symptoms. Further surveys, especially cohort studies and clinical trials are needed to confirm these results. |
| first_indexed | 2024-04-13T06:01:44Z |
| format | Article |
| id | doaj.art-ac6a961aa670438680e8b3dc43520142 |
| institution | Directory Open Access Journal |
| issn | 0147-6513 |
| language | English |
| last_indexed | 2024-04-13T06:01:44Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj.art-ac6a961aa670438680e8b3dc435201422022-12-22T02:59:24ZengElsevierEcotoxicology and Environmental Safety0147-65132022-09-01243113976Association of blood mercury exposure with depressive symptoms in the Chinese oldest oldJiahui Xiong0Yuebin Lv1Yuan Wei2Zuyun Liu3Xinwei Li4Jinhui Zhou5Yang Liu6Feng Zhao7Chen Chen8Heng Gu9Jun Wang10Xulin Zheng11Kai Xue12Yidan Qiu13Tong Shen14Xiaoming Shi15Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Jilin University, Changchun, Jilin 130021, ChinaSchool of Public Health, Zhejiang University, Hangzhou, Zhejiang 310058, ChinaSchool of Public Health, Jilin University, Changchun, Jilin 130021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Jilin University, Changchun, Jilin 130021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 210046, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Jilin University, Changchun, Jilin 130021, ChinaChina CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; School of Public Health, Zhejiang University, Hangzhou, Zhejiang 310058, ChinaDepartment of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Corresponding author.Department of Occupational Health and Environment Health, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China; Corresponding author at: China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.Depressive symptoms have a significant impact on the quality-of-life among the oldest old (aged ≥ 80 years) in the population. Current research on the association of blood mercury with depressive symptoms has mainly targeted the general population. However, it is unclear whether this association is present in the oldest old. We used data from the Healthy Aging and Biomarker Cohort Study carried out in 2017–2018, with 1154 participants aged ≥ 80 years eligible for analysis. Inductively coupled plasma mass spectrometry (ICP-MS) was employed to detect blood mercury (Hg) levels, while the CES-D10 depression scale was used to assess depressive symptoms. The association between blood mercury levels and depressive symptoms was investigated using log-binomial and Poisson regression models. We also used restricted cubic splines (RCS) to assess the linear or nonlinear association of blood mercury with depressive symptoms scores. The 1154 participants ranged in age from 80 to 120 years, while the geometric mean of blood mercury concentration was 1.01 μg/L. After adjustment for covariates, log-binomial and Poisson regression analyses revealed a statistically significant, positive association of blood mercury with depressive symptoms. In comparison to the first tertile, the adjusted relative risks of blood mercury and the presence of depressive symptoms in the second and third tertiles were 1.55 (1.20–1.99) and 1.45 (1.11–1.90), respectively. The RCS model showed a linear association between blood mercury level and depressive symptoms scores. In conclusion, among the oldest old, we demonstrated that blood mercury levels were positively associated with depressive symptoms. Further surveys, especially cohort studies and clinical trials are needed to confirm these results.http://www.sciencedirect.com/science/article/pii/S0147651322008168Depressive symptomsBlood mercuryThe oldest oldLog-binomial regression |
| spellingShingle | Jiahui Xiong Yuebin Lv Yuan Wei Zuyun Liu Xinwei Li Jinhui Zhou Yang Liu Feng Zhao Chen Chen Heng Gu Jun Wang Xulin Zheng Kai Xue Yidan Qiu Tong Shen Xiaoming Shi Association of blood mercury exposure with depressive symptoms in the Chinese oldest old Ecotoxicology and Environmental Safety Depressive symptoms Blood mercury The oldest old Log-binomial regression |
| title | Association of blood mercury exposure with depressive symptoms in the Chinese oldest old |
| title_full | Association of blood mercury exposure with depressive symptoms in the Chinese oldest old |
| title_fullStr | Association of blood mercury exposure with depressive symptoms in the Chinese oldest old |
| title_full_unstemmed | Association of blood mercury exposure with depressive symptoms in the Chinese oldest old |
| title_short | Association of blood mercury exposure with depressive symptoms in the Chinese oldest old |
| title_sort | association of blood mercury exposure with depressive symptoms in the chinese oldest old |
| topic | Depressive symptoms Blood mercury The oldest old Log-binomial regression |
| url | http://www.sciencedirect.com/science/article/pii/S0147651322008168 |
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