{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:20:02Z","timestamp":1787505602270,"version":"build-2736575974"},"reference-count":40,"publisher":"BMJ","funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72025402"],"award-info":[{"award-number":["72025402"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72072169"],"award-info":[{"award-number":["72072169"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["J Epidemiol Community Health"],"accepted":{"date-parts":[[2026,7,7]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Stress affects cardiometabolic health, but evidence linking objective, occupation-specific stressors to individual-level biomarkers (blood pressure, lipids) remains limited. Prior studies on market fluctuations mostly focus on macro outcomes (eg, population hospitalisations) or narrow samples, leaving gaps in understanding stress-driven metabolic changes in working populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used employee health examination data from all publicly listed financial firms in a provincial capital city in eastern China, covering the period from 1 October 2017 to 30 September 2023. It examined the associations between fluctuations in the stock returns of these firms and the blood pressure and lipid levels of their employees, employing restricted cubic splines and fixed-effects regression models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A 10% decline in a firm\u2019s daily stock return was associated with significant increases in several biomarkers: a rise of 3.054 mm Hg (95% CI 0.384 to 5.723; ~2.5%) in systolic blood pressure; 0.350 mmol\/L (95% CI 0.238 to 0.463; ~7.5%) in total cholesterol; 0.221 mmol\/L (95% CI 0.101 to 0.341; ~16.4%) in triglycerides; and 0.215 mmol\/L (95% CI 0.088 to 0.343; ~8.0%) in low-density lipoprotein cholesterol. Declines in returns had no significant effect on diastolic blood pressure or high-density lipoprotein cholesterol. Conversely, increases in stock returns showed no association with any measured biomarker. Crucially, these adverse health effects were observed exclusively among employees of financial firms; no such associations were found in the matched non-financial employee population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Stock return declines associate with metabolic disruptions in exposed employees. This study provides a generalisable framework for linking objective stressors to cardiometabolic health, informing cross-occupational health interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/jech-2025-225238","type":"journal-article","created":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T17:20:25Z","timestamp":1785172825000},"page":"jech-2025-225238","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["From market shocks to metabolic shocks: how acute workplace stress affects cardiometabolic biomarkers in employees"],"prefix":"10.1136","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9026-3348","authenticated-orcid":false,"given":"Yang","family":"Zhao","sequence":"first","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yina","family":"Li","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3588-1859","authenticated-orcid":false,"given":"Xing Lin","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiuchang","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Public Policy and Management, Tsinghua University, Beijing, China"},{"name":"Center for Crisis Management Research (Sponsored by Beijing Planning Office of Philosophy & Social Science), School of Public Policy & Management, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,7,27]]},"reference":[{"key":"2026072710201571000_jech-2025-225238v1.1","unstructured":"Institute for Health Metrics and Evaluation . 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