Work-attributed illness arising from excess heat exposure in Ontario, 2004-2010.
Fortune, Melanie K. ; Mustard, Cameron A. ; Etches, Jacob J.C. 等
Excess morbidity and mortality observed in recent decades during
extreme heat events in Europe and North America has called attention to
the environmental and occupational hazards associated with heat. (1)
Extreme heat exposures are projected to become more frequent due to
climate change. The Intergovernmental Panel on Climate Change estimates
that in the next three decades, North America will see mean temperature
increases of 1-3[degrees]C, alongside intensification of severe heat
waves. (2) By the 2050s and 2080s, heat-related population mortality is
estimated to increase by 70-90% and 120-140% respectively in
south-central Canada. (3)
Public health authorities have focused on addressing the
vulnerability of elderly persons and persons with chronic disease during
extreme heat episodes. Less attention has been paid to the surveillance
and management of occupational health risks arising from extreme heat
exposures. (4-6) Both outdoor and indoor working environments can have
high ambient temperatures due to weather variation and industrial
sources of heat in the absence of sufficient engineering temperature
controls. Protective equipment or clothing can inhibit the body's
ability to effectively cool in the work environment. (7) In addition,
work requiring physical exertion will generate additional metabolic
heat, even at moderate temperatures. (6,7)
Heat illnesses vary in severity, from heat cramps, heat edema and
heat syncope (fainting), to heat exhaustion and heat stroke, which can
lead to death. Heat stress can increase risk of other types of workplace
injuries due to impairment of physical and mental per formance. (7,8)
Previous research examining occupational heat illness has largely
been conducted in the United States and has focused on heat illness in
specific occupational groups, including military personnel, agricultural
workers and miners, (5,9-13) most frequently using workers'
compensation claim datasets. (9,11) The burden of illness related to
high ambient temperatures across all sectors of the labour force is not
well described and has not been examined for geographic areas in Canada.
(7) Given projected increases in heat hazards from climate change, an
increased understanding of this issue is critical to inform policies and
occupational health programming. The purpose of this study is to
describe the incidence of heat illness among occupationally-active
adults in the Canadian province of Ontario. The study makes use of two
population-based sources of data on incident heat illness: work-related
emergency department (ED) visit records and workers' compensation
lost time claim records. We assess the concordance of information in the
two datasets with a view that work-related ED records are more suited to
the surveillance of work-related heat illness than hospital admission or
mortality records due to their prompt sensitivity to meteorological
conditions. (14)
METHODS
Study objective and study design
The objective of this observational study was to estimate the
incidence rate of work illness arising from excess heat exposure in two
data sources for the Ontario labour force over a seven-year period.
Records of heat-related work-related illness for a complete population
of occupationally-active adults aged 15-64 years in the province of
Ontario were obtained from two independent sources: a census of allowed
lost time compensation claims registered with the Ontario Workplace
Safety & Insurance Board (WSIB) and a census of emergency department
encounter records where the illness was attributed to a workplace cause.
Included in this study are all individuals with an illness date from
January of 2004 to December of 2010.
Approval for this study was obtained from the University of Toronto
Health Sciences Research Ethics Board.
Data sources
National Ambulatory Care Reporting System (NACRS)
The Canadian Institute for Health Information (CIHI) is the
mandated repository for electronic records documenting visits to EDs in
acute care facilities in Ontario under the framework of the National
Ambulatory Care Reporting System (NACRS). (15) All Ontario citizens are
insured for medically necessary care, including care provided in acute
care hospital emergency departments. For this study, emergency
department records where the "responsibility for payment" code
indicated the WSIB were obtained from NACRS for the period January 2004
to December 2010. Responsibility for payment refers to the clinical
determination of a work-related cause of morbidity presenting to the
emergency department and is independent of the registration or
acceptance of a workers' compensation claim. (16) Variables
included in the extracted records were: gender, birth date, visit type,
visit date and a series of up to 10 fields documenting the main problem
and the external cause of injury. All unplanned ED visits were included
in the analysis. Data describing the reason for each visit is recorded
using the Canadian implementation of the International Classification of
Diseases, 10th Revision (ICD-10-CA).
Workplace Compensation Lost Time Claims
In Ontario, the WSIB is the sole provider of workplace compensation
coverage. Approximately 70% of the labour force is insured by the WSIB
based on firms' industrial characteristics; those not covered
include self-employed workers, domestic and casual workers and some
designated economic sectors (for example, financial and insurance
services). (17) Employees of insured firms are eligible for compensation
of lost wages and reimbursement of health care expenses resulting from a
work-related illness that required time to be taken off of work the day
after the injuring incident, under compensation known as lost time
claims. Electronic records of lost time claims include information on
the source, event and nature of occupational illness, classified
according to a standardized coding system. (18)
Measures
Case Definitions: Heat Illness
In ED records, a case of heat illness was defined on the basis of
ICD10-CA codes for conditions diagnosed as heatstroke, sunstroke, heat
collapse, heat cramps, heat exhaustion, heat fatigue, heat edema or
other effects of heat and light (Table 1). A visit was also classified
as a case of heat illness if a cause of the injury was "exposure to
natural heat".
Among lost time claims, a case of heat illness was defined by
information describing the nature, event or source of injury. If the
principal physical characteristics of the injury, its nature, included
effects of heat and light, the claim was defined as heat-related. This
encompassed heat stroke, heat syncope, heat fatigue, heat edema,
multiple effects of heat and light, unspecified effects of heat and
light, and effects of heat and light not classified elsewhere. Where the
source of injury, describing the exposure inflicting the injury, was
specified as environmental heat, sun or environmental temperature
extremes that were unspecified or not classified elsewhere, the claim
was defined as heat-related. Heat-relatedness was also attributed where
the event or exposure that resulted in the illness was listed as
exposure to environmental heat or contact with temperature extremes that
was unspecified or not classified elsewhere.
Occupation, Industry and Tenure of Employment
Information on occupation and industry of employment was available
only for lost time claims. Occupation is coded according to the National
Occupational Classification, 1991, (NOC) (19) and industry is classified
using the 1980 Standard Industrial Classification (SIC). (20)
Worker's employment tenure is the number of days between the
worker's initial employment and illness.
Labour Force Estimates
Denominator estimates of the number of full-time equivalent (FTE)
workers, stratified by age, gender, month and year for the Ontario
labour force were obtained from the Labour Force Survey conducted by
Statistics Canada. (21) Forty hours of work per week based on the actual
hours reported was considered to be the equivalent of a fulltime work
commitment. To accurately calculate rates of heat illness based on lost
time claims, estimates of the working population from the Labour Force
Survey were adjusted based on industry characteristics to determine the
number of FTE employees eligible for WSIB coverage. (17)
Analysis
Age, gender, year, month and age-/gender-specific rates of heat
illness were generated from both datasets. The distribution of heat
related illnesses on days throughout the seven-year period was examined,
considering the number of days over which all heat illnesses occur and
the adjacency of days with heat illnesses.
Rates of heat illness were calculated by dividing the number of
heat-related ED visits or lost time claims over the number of FTE
workers in Ontario eligible for each service. Rates were expressed per
1,000,000 FTE employee months. Confidence intervals consider variation
of the numerator only and were calculated using the normal approximation
method based on a Poisson distribution. (22) The characteristics of
workers with a heat illness documented in WSIB lost time claims were
described for industry and occupation. A number of occupational
exposures were attributed to individual claim records based on job
exposure matrices. The required skill level for the heat-injured
worker's occupation in addition to the physical job demands
(manual, mixed and non-manual) and environmental conditions relevant to
heat illness in their occupation were also described. Occupational
physical job demands were classified using methods developed by the
Institut de recherche Robert-Sauve en sante et en securite du travail.
(23) Worker's environmental condition classifications were coded
using the Human Resources and Skills Development Canada classifications,
which categorize hazards likely to be present in the occupational
environment and locations where the main duties of an occupation are
conducted (regulated inside climate, unregulated inside climate,
outdoors and/or vehicle). An unregulated inside climate describes the
presence of temperature or humidity levels considerably different from
normal room conditions. If an occupation lacks a regulated inside
climate (normal room conditions), no regulated inside climate was
indicated. (24)
The proportionate morbidity ratio (PMR) of heat-related lost time
claims relative to non-heat-related lost time claims was calculated for
all characteristics. Confidence intervals were calculated for incidence
rates. All analyses were conducting using SAS 9.3 and Microsoft Office
Excel 2007.
[FIGURE 1 OMITTED]
RESULTS
From 2004-2010, there were 785 heat-related visits to Ontario
emergency departments that were clinically attributed to work exposures
and there were 612 lost time claims identified as heat-related. The rate
of occupationally-attributed, heat-related ED visits was 1.6 per
1,000,000 FTE employee months (95% CI 1.5-1.7) and the rate of
heat-related lost time claims was 1.7 per 1,000,000 FTE employee months
(95% CI 1.6-1.9).
Unspecified heat exhaustion was the most frequent reason for an ED
visit (68%), while heat stroke and sunstroke represented 14% of visits.
Among lost time claims declared to be the effects of heat and light, 50%
of injuries were not classified, 18% were attributed to heat stroke, 10%
to heat fatigue and 6% to heat syncope. Monthly rates of
occupationally-attributed heat illness are less than one in a million
FTE employees from September to April, and incidence of heat illness is
highest in the June to August period in both data sources (Table 2).
Annual variation is also observed in both data sources, with elevated
incidence in 2005, 2006 and 2010.
Over the seven-year study period, the 785 ED visits for heat
illness occurred on 312 days (12% of all days in the seven-year
observation period). A total of 55% of all heat illnesses were clustered
in epidemics over contiguous days. Approximately 13% of all visits over
the seven-year period occurred on only two days in August of 2006.
WSIB lost time claims demonstrated similar clustering over time.
The 612 lost time claims occurred on 298 days (11% of all days in the
seven-year observation period). A total of 40% of all heat illnesses
were clustered in epidemics over contiguous days. Pronounced
concentration was also observed in this data source: 9% of illnesses
occurred on two days, one day in August 2006 and the other in July 2010.
The rates of ED visits and lost time claims were highest among
workers aged 15-24, although age differences were less pronounced among
lost time claimants (Figure 1). The incidence of heat illness was higher
among men in both data sources.
Table 3 reports the frequency of heat-related lost time claims by
industrial sector, occupational activity and skill level of
worker's position, as well as the PMR for these characteristics,
comparing those that are heat-related to all lost time claims. Among
heat-related lost time claims, the most frequent industrial sectors of
employment were Manufacturing (25%), Government Service (15%),
Construction (10%) and self-insured public sector employers (10%).
Relative to the proportion of all claims within each sector, there was a
higher proportion of heat-related claims in the following sectors:
Government (includes those working for school boards, power and
telecommunication lines, electric power generation, and municipal
services including waste management), Agriculture, Construction,
Business Services (includes employment agencies, technical and
professional services), Communication & Other Utility, self-insured
public sector employers, Manufacturing, Real Estate & Insurance
Agent, and Other Services (includes hospitality industries, janitorial
and repair industries as well as recreational services and facilities).
Among lost time claims, approximately two thirds of workers with
heat illnesses were in positions that were classified as manual labour
(Table 3). Relative to all lost time claims, there was a higher
proportion of heat-related claims among manual workers.
Table 3 also provides information on typical environmental working
conditions for the occupations of heat-injured workers with a lost time
claim. Approximately one half of workers with a lost time claim for heat
illness were employed in occupations with a prominent exposure to
outdoor work (PMR: 1.2), and approximately 25% were employed in
occupations that typically work in unregulated indoor environments (PMR:
1.5). Approximately 18% of workers with a lost time claim for heat
illness worked in occupations with typical exposure to fire, steam or
hot surface hazards at work (PMR: 1.5).
Approximately 70% of workers with heat-related lost time claims
were employed in the workplace for a year or more (Table 3). Workers
whose tenure was less than a month (PMR: 1.95) and from one to two
months (PMR: 1.53) experienced more heat claims relative to all claims.
With longer tenure, workers had proportionally fewer heat claims
relative to all claims.
DISCUSSION
In this study of occupational heat illness, two population-based
data sources provided concordant estimates of the incidence of heat
illness. The incidence of heat illness was concentrated among young men
and among manual occupations. Workers with less employment tenure had
proportionally more heat illness, as did those in industries with
substantial outdoor work. The absence of this pattern in smaller sectors
involving outdoor work, such as logging and forestry, is likely due to
lack of statistical precision. Further, proportionately more heat
illness was observed among workers in occupations with exposure to fire,
steam and hot surface hazards and in occupations with exposure to
unregulated indoor environments. Temporally, risk of heat illness was
greatest in the summer months, exhibited annual variation and was
clustered over contiguous days.
Approximately one sixth of the cases of heat illness ascertained in
this study were associated with a diagnosis of heat stroke, the most
severe heat illness that has an elevated risk of hospitalization and
death. (8) This proportion is comparable to hospitalization rates for
heat-affected workers in California. (25) A population-based examination
of heat illness in Washington State using workers' compensation
data from 1995-2005 observed 3.1 claims for heat illness annually per
100,000 FTE including no lost time claims and lost time claims. Had only
lost time claims been included, the rate would have been a tenth of that
observed in Ontario. (9) Comparing trends of heat illness by industrial
sector reveals similar patterns in Washington State as were noted in
Ontario, the exception being the state's Manufacturing sector,
which had proportionally fewer heat claims relative to all claims. (9)
These differences are likely attributable to regional differences in
climate, occupational demographics, prevention programming and claim
administration, and reinforce the need for region-specific understanding
of occupational heat illness.
We note a number of strengths of this study. The use of two data
population-based sources that have consistent methods for the
classification of work-related morbidity over the seven-year observation
period was an advantage for confirming observed patterns and trends. We
applied broad criteria for case ascertainment, including cases with
definitive diagnostic findings of heat illness and cases with suggestive
diagnostic classification. (14,25,26)
The study has a number of limitations. Although not incorporated in
this study, we anticipate that temperature, humidity and air pollution
measures available from meteorological sources would provide a more
refined analysis of risk estimates and may explain the annual variation
and clustering of heat illnesses observed over contiguous days. To
provide a simplistic example, on the day with the greatest burden of
heat illness, the maximum ambient temperature was 36[degrees]C in
Toronto and the Humidex peaked at 47[degrees]C, whereas the maximum
daily temperature and Humidex in the preceding week had a mean of
30[degrees]C and 39[degrees]C, respectively.
Additionally, the study is describing the incidence of heat illness
presenting to EDs or resulting in a workers' compensation lost time
claim. As such, we expect that the incidence rates reported in this
study underestimate the true burden of heat illness in this
jurisdiction. Drawing on studies of heat illness in the US states of
Washington and California, we might estimate that between 45-90% of
cases with less severe heat illness that do not require time off work do
not get reported in lost time compensation data. (9,25) While some of
this burden was likely captured in the ED encounters, cases treated in
primary care or workplace settings were excluded from this surveillance
study of the Ontario labour force.
Finally, we note that the study methods did not link individual
worker records between the ED data source and the workers'
compensation data source. The proportion of incident events that are
present in both data sources and that are uniquely present in each data
source are not estimated in this study.
In conclusion, this study of work-related heat illness events
provides information to inform occupational health services. The
evidence from this report suggests heat illness prevention programs
should target workers in manual occupations in typically outdoor
industries and workers in occupations with exposure to unregulated
indoor environments. Within these workplaces, younger individuals with
less workplace tenure would benefit most as they are unlikely to be
acclimatized to occupational conditions. Acknowledging that ambient heat
will become more severe in the coming decades, continuing efforts to
prevent work-related heat illness will be important.
REFERENCES
(1.) Kovats RS, Hajat S. Heat stress and public health: A critical
review. Annu Rev Public Health 2008; 29: 41-55.
(2.) Field CB, Mortsch LD, Brklacich M, Patz JA, Running SW, Scott
MJ. North America. In: Parry ML, Canziani OF, Palutikof JP, van der
Linden PJ, Hanson CE (Eds.), Climate Change 2007: Impacts, Adaptation
and Vulnerability. Contribution of Working Group II to the Fourth
Assessment Report of the Intergovernmental Panel on Climate Change.
Cambridge, UK: Cambridge University Press, 2007.
(3.) Cheng CS, Campbell M, Li Q Li G, Auld H, Day N, et al.
Differential and Combined Impacts of Winter and Summer Weather and Air
Pollution due to Global Warming on Human Mortality in South-central
Canada--Technical Report. Ottawa, ON: Health Canada, 2005.
(4.) Hanna EG, Kjellstrom T, Bennett C, Dear K. Climate change and
rising heat: Population health implications for working people in
Australia. Asia Pac J Public Health 2011; 23(2 Suppl): 14S-26S.
(5.) Jackson LL, Rosenberg HR. Preventing heat-related illness
among agricultural workers. J Agromedicine 2010; 15(3): 200-15.
(6.) Nelson NG, Collins CL, Comstock RD, McKenzie LB. Exertional
heat-related injuries treated in emergency departments in the U.S.,
1997-2006. Am J Prev Med 2011; 40(1): 54-60.
(7.) Jay O, Kenny GP. Heat exposure in the Canadian workplace. Am J
Ind Med 2010; 53(8): 842-53.
(8.) Health Canada. Extreme Heat Events Guidelines: Technical Guide
for Health Care Workers. Ottawa, ON: Health Canada, 2011.
(9.) Bonauto D, Anderson R, Rauser E, Burke B. Occupational heat
illness in Washington State, 1995-2005. Am J Ind Med 2007;
50(12):940-50.
(10.) Carter R, III, Cheuvront SN, Williams JO, Kolka MA,
Stephenson LA, Sawka MN, et al. Epidemiology of hospitalizations and
deaths from heat illness in soldiers. Med Sci Sports Exerc 2005; 37(8):
1338-44.
(11.) Donoghue AM. Heat illness in the U.S. mining industry. Am J
Ind Med 2004; 45(4): 351-56.
(12.) Howe AS, Boden BP. Heat-related illness in athletes. Am J
Sports Med 2007; 35(8): 1384-95.
(13.) Mirabelli MC, Quandt SA, Crain R, Grzywacz JG, Robinson EN,
Vallejos QM, et al. Symptoms of heat illness among Latino farm workers
in North Carolina. Am J Prev Med 2010; 39(5): 468-71.
(14.) Ye X, Wolff R, Yu W, Vanecekova P, Pan X, Tong S. Ambient
temperature and morbidity: A review of epidemiological evidence. Environ
Health Perspect 2012; 120(1): 19-28.
(15.) Canadian Institute for Health Information. Data Quality
Documentation: National Ambulatory Care Reporting System 2001-2002: For
External Users. Ottawa: CIHI, 2003.
(16.) Canadian Institute for Health Information. National
Ambulatory Care Reporting System Manual 2008-2009. Ottawa: CIHI, 2008.
(17.) Smith PM, Mustard CA, Payne JI. Methods for estimating the
labour force insured by the Ontario Workplace Safety & Insurance
Board: 1990-2000. Chronic Dis Can 2004; 25(3/4): 127-37.
(18.) Canadian Standards Association. Z-795-96 coding of work
injury or disease information. Etobicoke, ON: CSA, 1996.
(19.) Statistics Canada. National Occupational Classification
(NOC), 2011. Ottawa: Statistics Canada, 2012.
(20.) Statistics Canada. Standard Industrial Classification, 1980.
Ottawa: Statistics Canada, 1980.
(21.) Statistics Canada. Labour force survey estimates (LFS), job
tenure by type of work, sex and age group, annually (Persons). Ottawa:
Statistics Canada, 2012.
(22.) Byrne J, Kabaila P. Comparison of Poisson confidence
intervals. Comm Stat Theory Methods 2005; 34: 545-56.
(23.) Hebert F, Duguay P, Massicotte P, Levy M. Revision des
categories professionnelles utilisees dans les etudes de l'IRSST
portant sur les indicateurs quinquennaux de lesions professionnelles.
Montreal, QC: Institut de recherche Robert-Sauve en sante et en securite
du travail, 1996.
(24.) Human Resources and Skills Development Canada (HRSDC). Career
Handbook. Ottawa: Communication Canada, 2003.
(25.) Centers for Disease Control and Prevention. Fatalities from
occupational heat exposure. MMWR 1984; 33(28): 410-12.
(26.) Semenza JC, McCullough JE, Flanders WD, McGeehin MA, Lumpkin
JR. Excess hospital admissions during the July 1995 heat wave in
Chicago. Am J Prev Med 1999; 16(4): 269-77.
(27.) World Health Organization. International Statistical
Classification of Diseases and Related Health Problems, 10th Revision.
Malta: WHO, 2011.
(28.) Association of Workers Compensation Boards of Canada.
National Work Injury Statistics Program Code Standard NWIS (CSA Z795):
List of Code Titles for Code Variable: Source of Injury or Disease.
AWCBC, 2001.
(29.) Association of Workers Compensation Boards of Canada.
National Work Injury Statistics Program Code Standard NWIS (CSA Z795):
List of Code Titles for Code Variable: Nature of Injury or Disease.
AWCBC, 2001.
(30.) Association of Workers Compensation Boards of Canada.
National Work Injury Statistics Program Code Standard NWIS (CSA Z795):
List of Code Titles for Code Variable: Event or Exposure. AWCBC, 2001.
Received: April 12, 2013
Accepted: August 14, 2013
Melanie K. Fortune, mph, (1) Cameron A. Mustard, ScD, (1,2) Jacob
J.C. Etches, (PhD,1) Andrea G. Chambers, BHSc, MSc (1,2)
Author Affiliations
(1.) Institute for Work & Health, Toronto, ON
(2.) Dalla Lana School of Public Health, University of Toronto,
Toronto, ON
Correspondence: Dr. Cameron Mustard, Institute for Work &
Health, 481 University Avenue, Suite 800, Toronto, ON M5G 2E9, Tel:
416-927-2027, ext. 2143, Fax: 416-927-4167, E-mail: cmustard@iwh.on.ca
Sources of Support: Melanie Fortune was funded by a CIHR CGS
Scholarship as well as an Ontario Graduate Scholarship as a part of her
Master's work.
Conflict of Interest: None to declare.
Table 1. Inclusion and Exclusion Criteria for Case Definitions of Heat
Illness in Emergency Department (ED) Encounter Records and Lost Time
Claim Records
ED Encounter Records Lost Time Claim Records
ICD-10-CA Codes (27) Z795 Codes (28-30)
INCLUSION INCLUSION
Reason for Visit Nature of Injury
T67: Effects of heat 072: Effects of heat and light
and light
T67.0: Heatstroke 07200 Effects of heat and light, unspecified
and sunstroke
T67.1 Heat syncope 07210 Heat stroke
T67.2 Heat cramp 07220 Heat syncope
T67.3 Heat 07230 Heat fatigue
exhaustion,
anhydrotic
T67.4 Heat 07240 Heat edema
exhaustion due to
salt depletion
T67.5 Heat 07280 Multiple effects of heat and light
exhaustion,
unspecified
T67.6 Heat fatigue, 07290 Effects of heat and light, n.e.c.*
transient
T67.7 Heat oedema Event
T67.8 Other effects 32000 Contact with temperature extremes,
of heat and light unspecified
T67.9 Effect of heat 32100 Exposure to environmental heat
and light,
unspecified
X30: Exposure to 32900 Contact with temperature extremes,
excessive natural n.e.c.*
heat
Source of Injury
93600 Temperature extremes-environmental,
unspecified
93620 Heat-environmental
93690 Temperature extremes-environmental,
n.e.c.*
93920 Sun
EXCLUSION
071: Effects of reduced temperature
073: Effects of air pressure
* n.e.c.: not elsewhere classified.
Table 2. Incidence of Work-related Emergency Department (ED)
Encounters and Lost Time Claims Related to Excess Heat Exposure,
by Month, Year, Age and Gender, Ontario 2004-2010
ED Encounters Lost Time Claims
Number Incidence Rate Number Incidence Rate
of per 1,000,000 FTE of Events per 1,000,000 FTE
Events Months (95% CI) Months (95% CI)
Month
January < 5 0.1 (0.0-0.2) 5 0.2 (0.0-0.3)
February < 5 0.0 (0.0-0.1) 7 0.2 (0.1-0.4)
March < 5 0.1 (0.0-0.2) 6 0.2 (0.0-0.4)
April < 5 0.1 (0.0-0.2) 8 0.3 (0.1-0.5)
May 75 1.8 (1.4-2.2) 53 1.8 (1.3-2.3)
June 175 4.2 (3.5-4.8) 118 3.9 (3.2-4.6)
July 235 5.5 (4.8-6.2) 224 7.4 (6.4-8.3)
August 246 5.8 (5.1-6.5) 149 4.9 (4.1-5.7)
September 32 0.8 (0.5-1.0) 18 0.6 (0.3-0.9)
October < 5 0.1 (0.0-0.2) 14 0.5 (0.2-0.7)
November < 5 0.1 (0.0-0.2) 8 0.3 (0.1-0.5)
December < 5 0.0 (0.0-0.1) < 5 0.1 (0.0-0.2)
Year
2004 48 0.7 (0.5-0.9) 37 0.8 (0.5-1.0)
2005 166 2.4 (2.0-2.8) 155 3.1 (2.6-3.6)
2006 191 2.7 (2.3-3.1) 124 2.5 (2.0-2.9)
2007 132 1.8 (1.5-2.2) 93 1.8 (1.4-2.2)
2008 52 0.7 (0.5-0.9) 44 0.9 (0.6-1.1)
2009 54 0.8 (0.6-1.0) 42 0.8 (0.6-1.1)
2010 142 2.0 (1.7-2.3) 117 3.5 (1.9-5.1)
Age group
(years)
15-24 186 3.4 (2.9-3.9) 110 2.7 (2.2-3.2)
25-34 232 2.1 (1.9-2.4) 121 1.6 (1.3-1.9)
35-44 177 1.4 (1.2-1.6) 152 1.6 (1.4-1.9)
45-54 144 1.1 (1.0-1.3) 169 1.8 (1.6-2.1)
55-64 43 0.7 (0.5-0.9) 54 1.2 (0.9-1.5)
65+ < 5 0.3 (-0.1-0.7) 6 0.8 (0.2-1.5)
Gender
Male 612 2.2 (2.0-2.4) 419 1.9 (1.7-2.1)
Female 173 0.8 (0.7-0.9) 193 1.4 (1.2-1.6)
Incidence per 1,000,000 full-time equivalent (FTE) months, 95%
confidence intervals.
Table 3. Proportional Morbidity Ratios for Heat-related Lost Time
Claims in Ontario, 2004-2010, by Occupational Skill Type, Labour
Classification, Required Training Level, Environmental Conditions,
and Employment Tenure
Total Percent of Total Percent of PMR
Lost Lost Time Heat-related Heat-related
Time Claims (All Lost Time Lost Time
Claims Cause) Claims Claims
(All
Cause)
Industrial
sector
Government 35,834 6.3% 89 14.6% 2.31
service
Agriculture 5908 1.0% 12 2.0% 1.89
& related
services
Construction 41,101 7.2% 62 10.1% 1.40
Business 22,391 3.9% 33 5.4% 1.37
service
Communication 19,723 3.5% 27 4.4% 1.27
& other
utility
Self-insured 44,884 7.9% 61 10.0% 1.26
public sector
Manufacturing 122,524 21.6% 154 25.2% 1.17
Real estate 3300 0.6% < 5 0.7% 1.13
& insurance
agent
Other 18,757 3.3% 21 3.4% 1.04
services
Wholesale 29,146 5.1% 28 4.6% 0.89
trade
Logging & 1117 0.2% < 5 0.2% 0.83
forestry
Accommodation, 34,488 6.1% 30 4.9% 0.81
food &
beverage
Educational 13,625 2.4% 11 1.8% 0.75
service
Mining, 2607 0.5% < 5 0.3% 0.71
quarrying
& oil well
Transportation 40,557 7.1% 30 4.9% 0.69
& storage
Health & 62,724 11.0% 22 3.6% 0.33
social service
Retail trade 69,188 12.2% 24 3.9% 0.32
Fishing & 102 0.0% < 5 0.0% 0.00
trapping
Finance & 235 0.0% < 5 0.0% 0.00
insurance
Occupational
labour
classification
Manual 296,248 52.0% 364 59.5% 1.14
Mixed 186,153 32.7% 172 28.1% 0.86
Non-manual 68,906 12.1% 58 9.5% 0.78
Missing 17,815 3.1% 18 2.9% 0.94
Required
training level
for occupation
No training 131,759 23.1% 181 29.6% 1.28
required
College/ 135,469 23.8% 149 24.3% 1.02
apprenticeship
training
High-level 17,877 3.1% 18 2.9% 0.94
management
Secondary 241,053 42.4% 238 38.9% 0.92
school
Middle 10,851 1.9% 7 1.1% 0.60
management
Bachelor's 31,925 5.6% 19 3.1% 0.55
degree
Missing 188 0.0% <5 0.0% 0.00
Environmental
conditions in
occupation
Hazard: Fire, 64,869 11.4% 107 17.5% 1.53
steam, hot
surfaces
Location: 84,228 14.8% 138 22.5% 1.52
No regulated
inside
climate
Location: 205,040 36.0% 269 44.0% 1.22
Outside
Location: 130,271 22.9% 159 26.0% 1.14
Unregulated
inside
climate
Missing 32,448 5.7% 31 5.1% 0.89
Employment
tenure
< 1 month 23,833 4.2% 50 8.2% 1.95
1-2 months 33,437 5.9% 55 9.0% 1.53
3-5 months 35,475 6.2% 38 6.2% 1.00
6-11 months 46,463 8.2% 36 5.9% 0.72
[greater than 46,427 70.7% 399 65.2% 0.92
or equal to]
12 months
Missing 402,060 4.8% 34 5.6% 1.15
