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Chronic exposure to air pollution particles increases the risk of obesity and metabolic syndrome: findings from a natural experiment in Beijing
Open accessAbstract
Epidemiologic evidence suggests that air pollution is a risk factor for childhood obesity. Limited experimental data have shown that early‐life exposure to ambient particles either increases susceptibility to diet‐induced weight gain in adulthood or increases insulin resistance, adiposity, and inflammation. However, no data have directly supported a link between air pollution and non‐diet‐induced weight increases. In a rodent model, we found that breathing Beijing's highly polluted air resulted in weight gain and cardiorespiratory and metabolic dysfunction. Compared to those exposed to filtered air, pregnant rats exposed to unfiltered Beijing air were significantly heavier at the end of pregnancy. At 8 wk old, the offspring prenatally and postnatally exposed to unfiltered air were significantly heavier than those exposed to filtered air. In both rat dams and their offspring, after continuous exposure to unfiltered air we observed pronounced histologic evidence for both perivascular and peribronchial inflammation in the lungs, increased tissue and systemic oxidative stress, dyslipidemia, and an enhanced proinflammatory status of epididymal fat. Results suggest that TLR2/4‐dependent inflammatory activation and lipid oxidation in the lung can spill over systemically, leading to metabolic dysfunction and weight gain.—Wei, Y., Zhang, J., Li, Z., Gow, A., Chung, K. F., Hu, M., Sun, Z., Zeng, L., Zhu, T., Jia, G., Li, X., Duarte, M., Tang, X. Chronic exposure to air pollution particles increases the risk of obesity and metabolic syndrome: findings from a natural experiment in Beijing. FASEB J. 30, 2115–2122 (2016). www.fasebj.org
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“For instance, exposures have averaged around 16.8 ± 8.3 (SD) μg/m3 in São Paulo [53] to 73.5 ± 61.3 (SD) μg/m3 in Beijing [54].”
From Air pollution and children’s health—a review of adverse effects associated with prenatal exposure from fine to ultrafine particulate matter (2021) · cites this paper as [54]
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“Wei et al. [54] chronically exposed rats to either filtered or unfiltered polluted Beijing air throughout gestation to 8 weeks of age. Blood markers showed exposure to unfiltered air resulted in a worsened lipid profile, reduced GLP-1 levels, an incretin hormone that reinforces glucose-dependent secretion of insulin, and reduced antioxidant capacity parallel with measures of increased oxidative”
From Air pollution and children’s health—a review of adverse effects associated with prenatal exposure from fine to ultrafine particulate matter (2021) · cites this paper as [54]
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“Additionally, epididymal fat mass was greater in the male offspring exposed to polluted air.”
From Air pollution and children’s health—a review of adverse effects associated with prenatal exposure from fine to ultrafine particulate matter (2021) · cites this paper as [54]
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Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Brook, R. D., Rajagopalan, S., Pope, C. A., Brook, J. R., Bhatnagar, A., Diez-Roux, A. V., Holguin, F., Hong, Y., Luepker, R. V., Mittleman, M. A., et al. (2010) · Circulation · doi:10.1161/cir.0b013e3181dbece1 · Cited by 6,548
Elective induction versus spontaneous labor after sonographic diagnosis of fetal macrosomia.
Combs, C. A., Singh, N. B., & Khoury, J. C. (1993) · PubMed · Cited by 2,463
Obesity, Inflammation, and Insulin Resistance
Shoelson, S. E., Herrero, L., & Naaz, A. (2007) · Gastroenterology · doi:10.1053/j.gastro.2007.03.059 · Cited by 1,806
Tumor necrosis factor alpha inhibits signaling from the insulin receptor.
Hotamışlıgil, G. S., Murray, D. L., Choy, L., & Spiegelman, B. M. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.11.4854 · Cited by 1,220
Sun, Q., Yue, P., Deiuliis, J. A., Lumeng, C. N.-K., Kampfrath, T., Mikolaj, M. B., Cai, Y., Ostrowski, M. C., Lü, B., Parthasarathy, S., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.799015 · Cited by 765
Obesity‐induced inflammation: a metabolic dialogue in the language of inflammation
Ferrante, A. W. (2007) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2007.01852.x · Cited by 627
Air Pollution and Type 2 Diabetes
Rajagopalan, S., & Brook, R. D. (2012) · Diabetes · doi:10.2337/db12-0190 · Cited by 527
GeneMANIA Prediction Server 2013 Update
Zuberi, K., Franz, M., Rodriguez, H., Montojo, J., Lopes, C. T., Bader, G. D., & Morris, Q. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt533 · Cited by 396
Lee, Y.-S., Park, M.-S., Choung, J.-S., Kim, S.-S., Oh, H.-H., Choi, C.-S., Ha, S.-Y., Kang, Y., Kim, Y., & Jun, H.-S. (2012) · Diabetologia · doi:10.1007/s00125-012-2592-3 · Cited by 319
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Bowe, B., Xie, Y., Li, T., Yan, Y., Xian, H., & Al-Aly, Z. (2018) · The Lancet Planetary Health · doi:10.1016/s2542-5196(18)30140-2 · Cited by 371
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Johnson, N. M., Hoffmann, A. R., Behlen, J. C., Lau, C., Pendleton, D., Harvey, N., Shore, R., Li, Y., Chen, J., Tian, Y., et al. (2021) · Environmental Health and Preventive Medicine · doi:10.1186/s12199-021-00995-5 · Cited by 339
“[54] Sprague Dawley rats Ambient air 73.”
ResultFrank, L. D., Iroz‐Elardo, N., MacLeod, K. E., & Hong, A. (2019) · Journal of Transport & Health · doi:10.1016/j.jth.2018.11.008 · Cited by 289
Metadata
- Authors
- Wei, Y., Zhang, J. (., Li, Z., Gow, A., Chung, K. F., Hu, M., Sun, Z., Zeng, L., Zhu, T., Jia, G., Li, X., Duarte, M., & Tang, X.
- Affiliations
- Peking University (CN)
- Duke University (US)
- Chinese Research Academy of Environmental Sciences (CN)
- Rutgers, The State University of New Jersey (US)
- Imperial College London (GB)
- Beijing Institutes of Life Science, Chinese Academy of Sciences Beijing China
- Corresponding author
- Zhang, Junfeng (Jim)
- Tang, Xiaoyan
- ORCID
- Venue
- The FASEB Journal
- Publisher
- Wiley
- Published
- 2016-02-18
- Volume
- 30
- Issue
- 6
- Pages
- 2115-2122
- ISSN
- 0892-6638 (ISSN-L)
- 1530-6860
- PMC
- PMC6137545
- OpenAlex
- W2331479474
- Cited by
- 246
- References
- 24
- Citations by year
- 2026: 7 · 2025: 13 · 2024: 24 · 2023: 22 · 2022: 37 · 2021: 36 · 2020: 28 · 2019: 24 · 2018: 23 · 2017: 21 · 2016: 9
- FWCI
- 16.13
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- The FASEB Journal (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (21190051, 21477119)
- China Postdoctoral Science Foundation (201003010)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Toxic Organic Pollutants Impact
- Keywords
- air pollution, particulate matter, obesity, metabolic syndrome, prenatal exposure, postnatal exposure, rodent models, lung inflammation, oxidative stress, dyslipidemia, epididymal adipose tissue, TLR2/4, lipid oxidation, weight gain, Beijing air pollution
- MeSH terms
- Beijing, Air Pollution, Animals, Environmental Exposure, Female, Male, Obesity, Pregnancy, Prenatal Exposure Delayed Effects, Time Factors, Biomarkers, Rats, Sprague-Dawley, Metabolic Syndrome, Rats, Particulate Matter
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