| Literature DB >> 24366537 |
Jianjun Xiang1, Peng Bi, Dino Pisaniello, Alana Hansen.
Abstract
With predicted increasing frequency and intensity of extremely hot weather due to changing climate, workplace heat exposure is presenting an increasing challenge to occupational health and safety. This article aims to review the characteristics of workplace heat exposure in selected relatively high risk occupations, to summarize findings from published studies, and ultimately to provide suggestions for workplace heat exposure reduction, adaptations, and further research directions. All published epidemiological studies in the field of health impacts of workplace heat exposure for the period of January 1997 to April 2012 were reviewed. Finally, 55 original articles were identified. Manual workers who are exposed to extreme heat or work in hot environments may be at risk of heat stress, especially those in low-middle income countries in tropical regions. At risk workers include farmers, construction workers, fire-fighters, miners, soldiers, and manufacturing workers working around process-generated heat. The potential impacts of workplace heat exposure are to some extent underestimated due to the underreporting of heat illnesses. More studies are needed to quantify the extent to which high-risk manual workers are physiologically and psychologically affected by or behaviourally adapt to workplace heat exposure exacerbated by climate change.Entities:
Mesh:
Year: 2013 PMID: 24366537 PMCID: PMC4202759 DOI: 10.2486/indhealth.2012-0145
Source DB: PubMed Journal: Ind Health ISSN: 0019-8366 Impact factor: 2.179
Fig. 1.Process of selection of articles for inclusion in the review.
Summary of findings from surveillance data analysis articles on workplace heat exposure published between in January 1997–April 2012
| Data sources | Country | Data period | Target | Heat indices | Statistical analysis | Relationship between |
|---|---|---|---|---|---|---|
| The Australian Institute of Health and
Welfare | Australia | 2003–2004 | Athletes | Not used | Descriptive analysis | Not analysed |
| Hospital discharge data, New South Wales,
Australia | Australia | 2001–2004 | Athletes | Not used | Descriptive analysis | Not analysed |
| The medical centre of deep underground metal mine in
Australia | Australia | 1997–1998 | Miners | Dry bulb temp and WBGT1 | Descriptive analysis, U test | Not analysed |
| Hard coal mines in the Ruhr district,
Germany | Germany | 1995–1999 | Miners | Basic effective temp | Multivariate linear regression | U-shaped curve |
| Admission records of 5 hospitals, Central
Italy | Italy | 1998–2003 | All workers | Apparent temp | Poisson regression | Reversed U-shaped curve |
| The Washington State Department of Labour and
Industries’ State Fund, US | US | 1995–2005 | All workers | Not used | Descriptive analysis | Not analysed |
| The Agricultural Safety and Health Bureau of the North
Carolina Department of Labour, US | US | 1992–2006 | Farmers | Not used | Descriptive analysis | Not analysed |
| The US Bureau of Labour Statistics (BLS) Census of
Fatal Occupational Injuries (CFOI) | US | 2003–2008 | Farmers | Not used | Descriptive analysis | Not analysed |
| An aluminium smelting plant, US | US | 1997–1999 | Foundry workers | Dry bulb temp | Poisson regression | U-shaped curve |
| The US National Institute for Occupational Safety and
Health Website | US | 1983–2001 | Miners | Not used | Descriptive analysis, U-test, z-test | Not analysed |
| Total Army Injury and Health Outcomes Database, the US
Army Research Institute | US | 1980–2002 | Soldiers | Not used | Poisson regression | Not analysed |
| The Centre for Accession Research, US Army Accession
Command | US | 2005–2006 | Soldiers | Not used | Multiple logistic regression | Not analysed |
1WBGT denotes wet bulb globe temperature
Summary of epidemiological studies of workplace heat exposure published between January 1997–April 2012
| Target workers | Country | Sample size | Gender | Study design | Indoors or outdoors | Heat stress indices |
|---|---|---|---|---|---|---|
| All workers | Thailand | 40,913 | Both | Cohort | Both | Subjective symptoms |
| All workers | Thailand | 37,816 | Both | Cohort | Both | Subjective symptoms |
| Airport ground servicers | Saudi Arabia | - | - | Cross-sectional | Outdoor | WBGT |
| Construction workers | Japan | 319 | Male | Cross-sectional | Outdoor | WBGT |
| Construction workers | UAE1 | 150 | Male | Cross-sectional | Outdoor | TWL2 |
| Construction workers | India | 11 | Female | Cross-sectional | Outdoor | WBGT |
| Construction workers | Thailand | 108 | Both | Cross-sectional | Outdoor | WBGT |
| Construction workers | UAE1 | 22 | Male | Cross-sectional | Outdoor | TWL2, dry bulb temp |
| Construction workers | Japan | 12 | Male | Cross-sectional | Outdoor | WBGT |
| Construction workers | UAE1 | 44 | Male | Cross-sectional | Outdoor | - |
| Cooks | Japan | 12 | Male | Cross-sectional | Indoor | WBGT |
| Cooks | Japan | 809 | Both | Cross-sectional | Indoor | WBGT |
| Cooks | Japan | 16 | Male | Cross-sectional | Indoor | WBGT |
| Farmers | US | 300 | Both | Cross-sectional | Outdoor | Subjective symptoms |
| Farmers | Costa Rica | 42 | Male | Cross-sectional | Outdoor | Dry bulb temp |
| Farmers | India | 26 | Male | Cross-sectional | Outdoor | WBGT |
| Farmers | Costa Rica | 17 | Not indicated | Cross-sectional | Outdoor | Subjective symptoms |
| Fire fighters | Canada | 37 | Both | Experimental | Outdoor | Dry bulb temp |
| Fire fighters | Canada | 40 | Both | Experimental | Outdoor | Dry bulb temp |
| Fire fighters | US | 16 | Male | Experimental | Outdoor | Dry bulb temp |
| Forestry workers | Japan | 125 | Both | Cross-sectional | Outdoor | Subjective symptoms |
| Manufacturing workers | UAE1 | 275 | Not indicated | Cross-sectional | Indoor | WBGT |
| Foundry workers | US | 31 | Not indicated | Cross-sectional | Indoor | WBGT |
| Manufacturing workers | India | - | - | Cross-sectional | Indoor | WBGT |
| Manufacturing workers | India | - | - | Cross-sectional | Indoor | WBGT |
| Manufacturing workers | Bulgaria | 102 | Male | Cohort | Indoor | WBGT |
| Manufacturing workers | India | - | - | Cross-sectional | Indoor | WBGT |
| Manufacturing workers | India | 242 | Not indicated | Cross-sectional | Indoor | Subjective symptoms |
| Mine rescue workers | US | - | - | Cross-sectional | Indoor | WBGT |
| Mine rescue workers | Germany | 52 | Male | Cross-sectional | Indoor | Basic effective temp |
| Miners | Germany | 38 | Male | Cross-sectional | Indoor | Basic effective temp |
| Miners | Australia | 362 | Not indicated | Cross-sectional | Indoor | WBGT, TWL2 |
| Miners | Australia | 39 | Male | Cross-sectional | Indoor | WBGT, TWL2 |
| Miners | Australia | 36 | Male | Cross-sectional | Indoor | WBGT, TWL2 |
| Miners | Australia | 45 | Male | Cross-sectional | Indoor | WBGT, TWL2 |
| Mixed manual workers | South Africa | 151 | Both | Cross-sectional | Outdoor | Subjective symptoms |
| Mixed manual workers | Thailand | 21 | Both | Cross-sectional | Both | WBGT |
| Mixed manual workers | UAE1 | 186 | Male | Cross-sectional | Both | Urine gravity |
| Mixed manual workers | Australia | 29 | Male | Cross-sectional | Outdoor | Dry bulb temp |
| Soldiers | Australia | 64 | Male | Experimental | Outdoor | WBGT |
| Steel workers | Israel | 3,507 | Both | Cross-sectional | Indoor | Dry bulb temp |
| Steel workers | Taiwan, ROC | 55 | Male | Cross-sectional | Indoor | WBGT |
| Steel workers | Brazil | 8 | Male | Experimental | Indoor | WBGT |
1UAE: United Arab Emirates, 2TWL: thermal work limit