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.

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(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.

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(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.

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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: [email protected]

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