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The primary objective is to investigate the HGCZ\u2019s derivation process, its underlying data sources, and its effectiveness in predicting adverse health outcomes across various occupational environments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study examines the relationship between vibration metrics\u2014such as frequency-weighted acceleration and vibration dose value\u2014and reported musculoskeletal, neurological, and vascular outcomes, while also considering the role of individual confounding factors, including posture, age, and body mass index, in shaping exposure\u2013response relationships.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>HGCZ boundaries were identified as pragmatic expert compromises rather than being derived from quantitative dose\u2013response relationships. While the zone is a reasonable predictor for low back pain in seated operators, it lacks empirical support for neck, shoulder, or vascular outcomes. Analysis of aviation data showed that most flight scenarios reached caution thresholds significantly faster than traditional land-based driving, while individual factors such as posture and body mass index were found to modify actual health outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>We suggest the evolution of the HGCZ toward a probabilistic framework, where fixed thresholds are complemented by models linking exposure magnitude and duration to the likelihood of specific health outcomes (not only low back pain). Supported by biomechanical modelling and segment-specific frequency weightings, this approach would enable a more accurate assessment of WBV risk, extending rather than replacing the current framework.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00420-026-02236-0","type":"journal-article","created":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T10:07:33Z","timestamp":1788689253000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Scientific basis and applicability of the ISO 2631\u20131 health guidance caution zone"],"prefix":"10.1007","volume":"99","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2640-1764","authenticated-orcid":false,"given":"Marco","family":"Tarabini","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Genevieve","family":"Williams","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suzanne","family":"Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Setsuo","family":"Maeda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimo","family":"Bovenzi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"2236_CR1","doi-asserted-by":"publisher","DOI":"10.3390\/BUILDINGS14061713","author":"AJ Aguilar","year":"2024","unstructured":"Aguilar AJ, de la Hoz-Torres ML, Mart\u00ednez-Aires MD, Ruiz DP, Arezes P, Costa N (2024) Artificial neural network-based model for assessing the whole-body vibration of vehicle drivers. 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