Opportunities and Challenges From Leading Trends in a Biomonitoring Project
Canadian Health Measures Survey 2007–2017
Datos Bibliográficos
| ID | 22074382 |
|---|---|
| Autores | Yi‐Sheng Chao (0000-0002-4019-3586), Yi-Sheng Chao, Chao‐jung Wu (0000-0001-7156-1487), Chao-Jung Wu (0000-0002-8270-5498, Université du Québec à Montréal), Hsing‐Chien Wu (0000-0002-1762-5774, Taipei Hospital), Hsing-Chien Wu, Hui‐Ting Hsu (0000-0002-4230-4681, Changhua Christian Hospital), Hui-Ting Hsu, Lien-Cheng Tsao, Lien‐Cheng Tsao (0000-0002-2153-4517, Changhua Christian Hospital), Yen-Po Cheng (Changhua Christian Hospital), Yi-Chun Lai (0000-0002-4673-7492, National Yang Ming Chiao Tung University), Wei‐Chih Chen (0000-0003-4172-5529, Taipei Veterans General Hospital, autor de correspondencia), Wei-Chih Chen (0000-0003-4124-0222) |
| Año | 2020 |
| Volumen | 8 |
| Páginas | 460-460 |
| Fecha de publicación | 2020-09-09 |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Frontiers in Public Health (JOURNAL) |
| Identificadores de la revista | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Editorial | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2020.00460 |
| PMID | 33014969 |
| OpenAlex | W3084295439 |
| Idioma | EN |
| Referencias citadas | 20 |
Background Biomonitoring can be conducted via the assessment of the levels of chemicals in human bodies and their surroundings, for example, as in the Canadian Health Measures Survey (CHMS). This study aims to report the leading increasing or decreasing biomarker trends and determine their significance. Methods We implemented a trend analysis for all variables from the CHMS biomonitoring data cycles 1 to 5 conducted between 2007 and 2017. The associations with time and obesity were determined with linear regressions using the CHMS cycles and body mass index (BMI) as predictors. Results There were 997 unique biomarkers identified and 86 biomarkers with significant trends across cycles. Nine of the ten leading biomarkers with the largest decreases were environmental chemicals, and the levels of 1,2,3-trimethylbenzene, dodecane, palmitoleic acid, and o-xylene decreased by more than 60%. All of the ten chemicals with the largest increases were environmental chemicals, and the levels of 1,2,4-trimethylbenzene, nonanal, and 4-methyl-2-pentanone increased by more than 200%. None of the twenty biomarkers with the largest increases or decreases between cycles were associated with BMI. Conclusions Opportunities in the CHMS include the feasibility of determining the associations between biomarkers and time or BMI. The challenges include the unknown causes of trends with large magnitudes of increase or decrease and their unclear impact on Canadians’ health. We recommend that the CHMS to plan future cycles with reference to the leading trends and to measure chemicals with both human and environmental samples
Biology · Biomarker · Biomonitoring · Environmental health · Exposome · Chemistry · Climate Change and Health Impacts · Effects and risks of endocrine disrupting chemicals · Environmental Science · Health, Environment, Cognitive Aging · Medicine · Environmental Chemistry
| Altamente citado | No |
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