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Background <p>With limited access to mental health specialists for diagnosis, current stress tracking methods rely on questionnaire results. These self-report questionnaires often obtain untruthful answers, especially in beneficial situations such as career hiring or promotion. This study aimed to evaluate an alternative method for stress screening based on analysis of sweat volatile organic compounds.</p> Methods <p>Sweat samples of 44 firefighters were collected using headspace-solid phase microextraction (HS-SPME). Sweat VOCs were analyzed using gas chromatography-mass spectrometry (GC-MS). The compounds were identified by comparing the experimental retention indices (<i>I</i>) and MS spectra with the database from the National Institute of Standards and Technology (NIST) library.</p> Results <p>The obtained data were correlated with the standardized questionnaire-based Thai version of the perceived stress scores (T-PSS-10) of the volunteers. The significant peaks were then selected based on the individual accuracy and <i>t</i>-test. Six possible volatile features for high stress (PSS score ≥ 32) samples were revealed. Their potential sources could involve human and microbiome metabolism/catabolism. By using partial least square discriminant analysis (PLS-DA), these markers could be combined into a single feature. The feature value thresholds were then varied for construction of receiver operating characteristic (ROC) curves. With the optimum threshold, the combined marker offered the accuracy, sensitivity, selectivity and area under curve (AUC) of 84%, 87%, 81% and 91%, respectively.</p> Conclusions <p>This pilot study demonstrates the feasibility of using sweat VOC profiling via HS-SPME GC-MS as a rapid and non-invasive method for occupational stress screening. The technique provides objective biochemical markers that could enhance the reliability of conventional questionnaire-based assessments in high-risk occupational groups.</p>

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Metabolomic profiling of sweat VOCs for occupational stress surveillance in firefighters: a GC-MS pilot study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月20日

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  • Teerada Somphot,
  • Thanaphol Sirithaweesuk,
  • Luxsana Dubas,
  • Nuttanee Tungkijanansin,
  • Chavit Tunvirachaisakul,
  • Michael Maes,
  • Patthrarawalai Sirinara,
  • Chadin Kulsing

摘要

Background

With limited access to mental health specialists for diagnosis, current stress tracking methods rely on questionnaire results. These self-report questionnaires often obtain untruthful answers, especially in beneficial situations such as career hiring or promotion. This study aimed to evaluate an alternative method for stress screening based on analysis of sweat volatile organic compounds.

Methods

Sweat samples of 44 firefighters were collected using headspace-solid phase microextraction (HS-SPME). Sweat VOCs were analyzed using gas chromatography-mass spectrometry (GC-MS). The compounds were identified by comparing the experimental retention indices (I) and MS spectra with the database from the National Institute of Standards and Technology (NIST) library.

Results

The obtained data were correlated with the standardized questionnaire-based Thai version of the perceived stress scores (T-PSS-10) of the volunteers. The significant peaks were then selected based on the individual accuracy and t-test. Six possible volatile features for high stress (PSS score ≥ 32) samples were revealed. Their potential sources could involve human and microbiome metabolism/catabolism. By using partial least square discriminant analysis (PLS-DA), these markers could be combined into a single feature. The feature value thresholds were then varied for construction of receiver operating characteristic (ROC) curves. With the optimum threshold, the combined marker offered the accuracy, sensitivity, selectivity and area under curve (AUC) of 84%, 87%, 81% and 91%, respectively.

Conclusions

This pilot study demonstrates the feasibility of using sweat VOC profiling via HS-SPME GC-MS as a rapid and non-invasive method for occupational stress screening. The technique provides objective biochemical markers that could enhance the reliability of conventional questionnaire-based assessments in high-risk occupational groups.