Volume 25
Number 3/4
2004

[Table of Contents]

Methods for estimating the labour force insured by the Ontario Workplace Safety & Insurance Board: 1990-2000

Peter M Smith, Cameron A Mustard and Jennifer I Payne

Abstract

This paper presents a methodology for estimating the size and composition of the Ontario labour force eligible for coverage under the Ontario Workplace Safety & Insurance Act (WSIA). Using customized tabulations from Statistics Canada's Labour Force Survey (LFS), we made adjustments for self-employment, unemployment, part-time employment and employment in specific industrial sectors excluded from insurance coverage under the WSIA. Each adjustment to the LFS reduced the estimates of the insured labour force relative to the total Ontario labour force. These estimates were then developed for major occupational and industrial groups stratified by gender. Additional estimates created to test assumptions used in the methodology produced similar results. The methods described in this paper advance those previously used to estimate the insured labour force, providing researchers with a useful tool to describe trends in the rate of injury across differing occupational, industrial and gender groups in Ontario.

Key words: denominators; Labour Force Survey; Ontario Workplace Safety & Insurance Board coverage; surveillance; work-related injury

Introduction

Between 1991 and 2000, the annual number of lost-time work-related injuries reported to the Ontario Workplace Safety and Insurance Board (WSIB) declined by approximately 32%, from 155,500 to 104,000.¹ However, understanding whether there has been a reduction in work-related injury rates, and whether these reductions are consistent across population subgroups (i.e., younger age groups, short-tenure employees, female workers and different occupational groups) has been hampered by the absence of accurate denominators describing these key dimensions of the insured workforce in Ontario.

The WSIB estimates the proportion of Ontario labour force participants it insures using reported payrolls from employers who pay insurance premiums. This estimate was not designed for research use, however, and it is limited in three key ways:

1. These estimates are only reported across each of the WSIB 16 major industry sectors (WSIBIS). Information on other equally important subgroups for work-related injury analysis such as occupation,^2,3 gender³ and hours of work per week⁴ are not included in the payroll database.
2. The estimates represent only the employees covered under one of the two WSIB insurance schedules,^5,a although injury claim data is available for employees covered under both schedules.
3. Since the individual salaries^b of employees and total payrolls were used to create these estimates, not the actual number of employees, they may not provide an accurate reflection of the total number of people insured by the WSIB.

Given the limitations in the WSIB payroll data estimates, research on the epidemiology of work-related injury in Ontario has most commonly opted to use alternate sources to calculate injury rates. Rael,^6,7 and Brooker and colleagues,⁸ have both used LFS and Census data to generate denominator counts for injury rate calculations within speciWc industry and occupational subgroups. Both approaches adjust the LFS data to exclude the self-employed population^c and those labour force participants who were unpaid family workers, as these groups are excluded from coverage under the WSIA.

Zakaria and colleagues⁴ have extended these methods, proposing that calculation of LFS counts should be reported as Full-Time Equivalents (FTEs)^d, using reported hours usually worked per week. Adjusting for hours worked per week provides more accurate estimates of exposure time in estimating injury risk in female and youth population groups, which are more likely to work part-time. To date, Zakaria has only used these methods to generate estimates for the entire labour force population in Ontario.

Removing the self-employed population and unpaid family workers, however, does not fully capture Ontario's complicated work-related injury legislation. The majority of companies in Ontario have mandatory coverage for workplace injuries from the WSIB, for which they in return pay insurance premiums. However, there are two other groups of insurance coverage in Ontario. Some companies (predominantly educational institutions and municipal and regional government agencies) are covered under an alternate insurance schedule, referred to as "schedule 2". These companies do not pay insurance premiums, but are still required to report all workplace injuries to the WSIB. Other companies have optional coverage; it is not mandatory that they pay premiums to the WSIB. These companies can cover their employees with the WSIB if they so choose. This group includes employees engaged in barbering, shoe shining, veterinary work, in the offices of dentists, physicians and lawyers, in funeral directing and embalming, photography, and in the majority of the finance and insurance industries.^5,9 Other labour force participants without mandatory insurance coverage include casual employees and people who work off-site. Therefore, only permanent, on-site employees working for companies covered under either schedule 1 or schedule 2 must report injuries to the WSIB.

Business fit into one of these three groups depending on the industry in which they primarily operate. The WSIB groups companies in Ontario into over 800 different industry segments, referred to as classification units (CU).¹⁰ Each CU is directly comparable to the most detailed level of the Standard Industrial Codes 1980 (SIC80), the primary industrial grouping used by Statistics Canada. The structure of the SIC80 is presented in Figure 1.

FIGURE 1
The structure of the standard industrial code 1980

It should be possible to determine the proportion of the labour force insured by the WSIB with population-based data at the SIC unit group level. Unfortunately, differentiation of industry segments within population level surveys such as the Labour Force Survey and Census only occurs at the level of the 318 minor groups contained in the SIC80 (three-digit level). Within a given three-digit minor group, some of the four-digit unit groups may be compulsorily covered, and others may have optional coverage.^e Therefore, each of the three-digit minor groups of the SIC80 can be assigned to one of the following three categories:

1. Those composed of four-digit unit groups which all must report workplace injuries to the WSIB (235 [74%] of the 318 minor groups).
2. Those composed of four-digit unit groups with mandatory insurance coverage, and others with optional insurance coverage (41 of the 318 minor groups).
3. Those composed of four-digit unit groups all with optional insurance coverage with the WSIB (42 of the 318 minor groups).

In this paper we propose to build on previous attempts to estimate the size and composition of the insured labour force in Ontario. Following Rael^6,7 and Brooker⁸ we will use LFS and Census counts, adjusted for the self-employed population and unpaid family workers. Following Zakaria,⁴ we will present our denominator counts as full-time equivalents. However, in addition we will adjust our LFS counts for industry groups with optional WSIB coverage and groups with mixed coverage. We will compare these estimates, at an aggregate level, to estimates of the total labour force and the non-self-employed labour force. We will further present these estimates across all major occupational and industrial groups, stratiWed by gender. We will examine the sensitivity of our estimates using alternate assumptions. Finally, we will demonstrate the utility of these denominators by presenting a series of injury rates, using WSIB injury claim data as the numerator, with a series of alternate denominator estimates.

Data sources for Ontario labour force estimates

The Labour Force Survey (LFS)

Coverage

The LFS, conducted by Statistics Canada, produces estimates of the working-age population (employed, unemployed and non-labour force participants) using a sample of less than 1% of the Canadian population. The LFS follows a complex, rotating panel sample designed to efficiently estimate month-to-month changes in the Canadian labour force.¹¹

Measures

Important variables included in the LFS are labour force participation; gender; age; usual working hours per week; occupation; and industry.

Data available

Statistics Canada provided custom tabulations of the Ontario labour force by occupation, coded to the Standard Occupational Code 1991 (SOC91) at the three-digit level (139 separate groups), stratified by gender, labour force status (self employed versus not self employed) and hours of work (full-time versus part-time) for the years 1990 through 2000.

Canadian Census data

Coverage

The Canadian Census long form samples approximately 20% of the Canadian population and collects information on different types of labour force participation.

Measures

The Census gathers information on labour force participation over the previous seven days, as well as information on occupation, industry, gender, age and hours usually worked per week. Due to its larger sample size, the Census is able to report occupation at a more detailed (four-digit) level than that provided in the LFS, which is reported at the three-digit level.

Data available

We obtained data from the 1991 and 1996 Census by SOC91 at the four-digit level (503 separate groups), stratiWed by gender. We also had a matrix of three-digit SOC91 (139 groups), by three-digit Standard Industrial Code 1980 (SIC80) (296 groups^6,f) for both 1991 and 1996.

Table 1 provides a description of the data from the LFS and Census used in the calculation of our denominator estimates.

A summary of the measures included in our estimates of the Ontario labour force from the sources listed above are described in Table 2. The information provided in the WSIB injury claims, and from the WSIB payroll denominators, are also included for comparison purposes.

TABLE 1
Data available from the LFS and Census for the calculation of denominators for the Ontario labour force

TABLE 2
Summary of variables available within different Ontario injury and labour force data sources, 1990-2000

Methods and analysis

Our main study objective was to create a series of denominators that could be used in conjunction with WSIB lost-time injury reports in Ontario, using the LFS and Census. These denominators would be stratified by the major occupational and industrial groups, as well as gender. A secondary objective was to investigate the reliability of our estimates by comparing them to alternative estimates generated using different assumptions.

Steps for estimating the insured labour force by gender and occupation

A flowchart describing each of the steps below is presented in Figure 2.

1. The initial adjustment made to the LFS counts was the removal of self-employed labour force participants. This was done at the three-digit occupational level.
2. The non-self-employed population was then separated into four groups on the basis of gender and hours of work. These were males working full-time (MFT), males working part-time (MPT), females working full-time (FFT) and females working part-time (FPT). Because the self-employed labour force counts were not stratified by full-time and part-time status, this step assumed that the proportions of full-time to part-time labour force participants are similar in both the self-employed and non-self-employed populations.
3. To adjust the LFS counts for industries likely excluded from insurance coverage required that the occupational counts be converted to industrial counts. This conversion used the matrix from the 1991 and 1996 census of three-digit SOC91 and three-digit SIC80. For the years 1992-1995 a proportional matrix, based on the 1991 and 1996 matrix was calculated. For the years 1997 through 2000, the 1996 matrix was used. Using this matrix the four gender X employment status groups were converted from three-digit SOC91 to three-digit SIC80.

FIGURE 2
Steps for estimating the insured labour force in Ontario

4. To accurately estimate the population required to report work injuries only those three-digit minor groups of the SIC80 composed of four-digit unit groups required to report injuries were kept. The minor groups of the SIC80 with mixed coverage (some four-digit unit groups in schedule 1 and/or schedule 2 and others with optional coverage) are listed in Appendix I. Those three-digit SIC80 groups with only voluntary coverage requirements are listed in Appendix II.
5. Using the same SIC80 X SOC91 matrices, each three-digit SOC91 count was then collapsed into one of the 10 different one-digit major occupational groups. At the completion of this step we had our four gender X employment status groups, stratiWed by 10 major occupational groups.
6. The final adjustment was to weight each full-time and part-time labour force participant as a FTE. These weights were generated using the public use Wles of the LFS and are presented in Table 3.

TABLE 3
Full-time equivalent weights for full-time and part-time labour force participants stratified by gender, 1990-2000

Steps for estimating the insured labour force by gender and industry

To estimate the insured labour force by industry and gender, steps 1 through 4 from the occupation and gender estimation were followed.

1. Each three-digit minor group from the SIC80 was collapsed into one of the 18 major industrial groups. Some of the major industrial groups were very small in size. Where counts within an industrial group were less than 4,000, the estimates were suppressed.
2. To create a comparable series of FTE counts, each full-time and part-time labour force participant was assigned a full-time equivalent weight using the same methods used to generate the occupational estimates.

Sensitivity analyses

To test the reliability of our denominator estimates and to reflect the assumptions we used in their generation, we tested two alternate methods and compared these to our original estimates:

1. In step 2 the gender X employment status groups were generated assuming the ratio of full-time to part-time labour force participants was the same in the employed and self-employed populations. We sought to examine how much the FTE estimates for each major occupational and industrial group would change if we assumed that all the self-employed population was working full-time.
2. A relevant issue, given the nature of the LFS, was the accuracy of the annual estimate of the Ontario labour force. As quarterly estimates were also available, we investigated changes in FTE estimates across major occupational and industrial groups when using high and low quarterly three-digit occupational counts.

Results

Objective one: Comparing aggregate LFS estimates after adjustments for excluded groups and hours of work, 1990-2000

Table 4 presents the total labour force counts after each adjustment described in the methods, as well as the final aggregate FTE estimates. Between 1990 and 2000, 65% - 68% of the non-self-employed labour force worked in industry groups with mandatory insurance coverage.

TABLE 4
Comparing estimates from the LFS after adjustments for self-employed population and those industry groups with mixed or voluntary insurance coverage, 1990-2000

Objective two: Creation of a series of denominators for the mandatorily insured labour force by major occupational and industrial group stratified by gender

Table 5 presents the total person count and total full-time equivalent count for the insured Ontario labour force, by major SOC91 group, stratified by gender for the year 2000. Given the larger percentage of females working part-time, the differences after adjusting total counts for hours worked per week (FTEs) were greater in the female population than the male population.

TABLE 5
Estimates of the mandatorily insured labour force in Ontario stratified by occupational group and gender, 2000 only

Table 6 presents the same series of estimates separately for male and female labour force participants, stratified by major SIC80 industrial group. Industrial sector counts below 5,000 FTEs were suppressed.

TABLE 6
Estimates of the mandatorily insured labour force in Ontario stratified by industrial group and gender, 2000 only

Objective three: Examining the sensitivity of the mandatorily covered labour force estimates

Differences in the FTE estimates under the assumption that all self-employed labour force participants work full-time were minor. For both men and women, the largest differences were observed in primary industries and the occupational groups of management, health, and trade and transport.

Differences relative to seasonal variation in employment were more substantial. For both men and women the largest differences were reported in the agriculture, logging and forestry industries. The largest occupational changes were in occupations unique to primary industry and art, culture, recreation and sport. These tables are not included, but available upon request from the authors.

Objective four: Calculation of injury rates using WSIB injury claim data and alternate denominator estimates

Table 7 presents injury rates by occupation and gender groups using different denominator estimates. The absolute change in injury rate between different denominator estimates is also presented. Removal of the self-employed population results in higher injury rate estimates across all occupation and gender groups.

Restricting both lost-time injury claims and denominator estimates to include only those industry groups with mandatory insurance coverage resulted in an overall increase in injury rate estimates in both males and females. However, decreases in injury rates were observed between particular occupational groups, such as sales and service occupations, trade, transport and equipment operators, and occupations unique to processing, manufacturing and utilities.

Calculating rates of lost-time injuries per 1,000 full-time equivalents produced greater increases in female injury rates compared to males due to the higher percentage of females who are part-time labour force participants.

TABLE 7
Comparing lost-time injury rates across gender and occupational groups using different denominator estimates, 2000 only

Discussion

From the results of this paper we suggest that a series of equally important adjustments should be made to LFS and Census data if they are to be used to provide denominator estimates for WSIB lost-time injury data numerators. At the aggregate level each of our adjustments to the LFS increased the injury rate across both males and females. We believe this methodology enables a more accurate picture of the size and distribution of the insured labour force in Ontario across major occupational and industrial groups.

Direct comparison with our results and those of Rael^6,7 and Brooker⁸ are not possible due to different year of study in the case of Rael and the presentation of rate information in the case of Brooker. Our fully adjusted denominator estimates are approximately 28% lower than those previously presented by Zakaria,⁴ reflecting the exclusion of industrial groups with either mixed or voluntary insurance coverage.

These estimates should be interpreted in light of the following limitations. Part-time labour force participants were given a uniform weighting for the calculation of FTEs. It is likely that the total hours worked per week by part-time labour force participants differs across occupation and industry groups. Using Zakaria et al.'s⁴ formula to determine the hours usually worked per week by each part-time labour force participant will provide greater accuracy.

Neither our LFS counts of the self-employed population, nor the matrix of occupation and industry were stratified by gender. Differences in female and male labour force participation across each of these areas may reduce the validity of our estimates. Future studies using denominator estimates should endeavour to obtain initial LFS and Census counts stratified by gender, with the self-employed population already removed.

There are a number of strengths in the denominator series produced by these methods. In spite of the limitations listed above, sensitivity analyses of the assumptions concerning self-employment and seasonality did not unearth serious limitations in estimates for either men or women.

Our confidence in the validity of these estimates, at the aggregate level, is further strengthened in assessing the injury rates within each of the subgroups of insurance coverage (mandatory coverage versus mixed insurance coverage versus no insurance coverage). After standardizing rates for different gender and industry compositions, the rate in the mandatory coverage group was 23.7 per 1,000 FTE's. Within the mixed group, where we would expect injury reports to be fewer given that some companies are mandated to report injuries, the injury rate per 1,000 FTE's was 19.8. Finally, the voluntary coverage group, where the number of injury reports should be the lowest, had a injury rate of 6.8 per 1,000 FTE's.

The rates and relative risks, presented in Table 7 demonstrate the importance of accurate denominators to calculate injury rates. Adjustment for labour force participants with either uncertain or voluntary insurance coverage increased the overall injury rate in men by 10 injuries per 1,000 FTE's, with a similar absolute increase in the predicted injury rate for women.

Further, injury rates in particular occupational groups were more sensitive to the labour force survey adjustments. The rate of injury for males working in occupations in art, culture, recreation and sport, and occupations unique to primary industry, both increased by over 100%. Rates of injuries for males in health care occupations increased by 94%, teachers and professors increased by 77%, management occupations by 74%, and occupations in business and finance by 55%. Similarly, injury rates for females in art, culture, recreation and sport (167%), management occupations (108%), primary industry occupations (97%), and those in business and finance (60%) all substantially increased.

Suggested guidelines for the use of denominator data with WSIB injury claim numerators

While these methods have a wide range of possible applications for research on work-related injury in Ontario, we make the following suggestions regarding their use in calculating injury claim rates:

1. With each level of increased detail there is an increased risk of inaccuracy in the concordance between WSIB injury claim data and LFS occupational and industrial classification estimates. Therefore we recommend the use of denominators only by major occupational and industrial groups.
2. Where possible, particularly in relation to industrial groups, we recommend combining smaller groups (e.g., fishing and trapping with logging and forestry) to make larger groups.
3. When reporting injury rates for two different groups (e.g., males and females) we suggest emphasizing differences in relative risks between groups as opposed to actual claim and denominator numbers, as any measurement errors in the calculation of injury rates are likely to be randomly distributed across genders.
4. The denominator estimates and injury counts used in this paper are for both the schedule 1 and schedule 2 insured labour force. It has been suggested, due to differences in the direct cost burden for injured employees, that the claim management process may differ between the two schedules. We therefore recommend caution when comparing rates in occupational or industrial groups that may contain a large proportion of schedule 2 employees (e.g., education and government service industries and occupational groups of teachers and professors) with other groupings of employees.

Conclusion

We feel that the methods used in this paper have advanced previously used methods for the calculation of the insured labour force in Ontario. By using these methods, researchers will be able to describe the epidemiology of injury across different occupational, industrial and gender strata, both cross-sectionally and over time.

Acknowledgements

Special thanks to Marjan Vidmar, who extracted the information from the WSIB administrative records that were used in this paper.

References

1. Workplace Safety & Insurance Board of Ontario. Statistical supplement to the annual report 2000. Technical report. Workplace Safety & Insurance Board of Ontario, Toronto, Ontario, 2001.
2. DeLeire T, Levy H. Gender, occupation choice and the risk of death at work. Working Paper 8574, National Bureau of Economic Research, Cambridge, MA, 2001.
3. Messing K. One-eyed science: Occupational health and women workers. Labour and social change. Temple UP, Philadelphia, 1998.
4. Zakaria D, Robertson J, MacDermid JC, Hartford K, Koval J. Estimating the population at risk for Ontario Workplace Safety and Insurance Board covered injuries or diseases. Chronic Dis Can 2002;23(1):17-22.
5. Workplace Safety & Insurance Board of Ontario. Coverage under the Ontario Work-place Safety & Insurance Act. Technical report. Workplace Safety & Insurance Board of Ontario, Toronto, Ontario, 2002.
6. Rael EGS, Badley E, Frank JW, Shannon HS. Applying and expanding Haggar Guenette's method of using labour force survey paid workers as denominators. Report 1994.
7. Rael EGS, Badley EM, Frank JW, Shannon HS. Using labour force survey and census data to generate denominators for occupational injury rates: An application and expansion of Haggar Guenette's method. Chronic Dis Can 1996; 17(3/4):87-91.
8. Brooker AS, Frank JW, Tarasuk VS. Back pain claim rates and the business cycle. Social Science & Medicine, 1997;45(3):429-39.
9. Statutes of Ontario. Workplace Safety & Insurance Act. Bill/Resolution, 1997.
10. Workplace Safety & Insurance Board of Ontario. WSIB Employer Classification Manual. Technical report, Ontario, Statistics Canada, 2003.
11. A guide to the Labour Force Survey, number 71543GIE, pages 1-38. Minister of Industry, Ottawa, 2003.

Notes

APPENDIX I

Minor groups from the Standard Industrial Classification (1980) with mixed insurance coverage

APPENDIX II

Minor groups from the Standard Industrial Classification (1980) with only voluntary insurance coverage

Author References

Peter M Smith, Institute for Work & Health, Toronto, Ontario, Canada

Cameron A Mustard, Institute for Work & Health and Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada

Jennifer I Payne, Cancer Care Ontario and Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada

Correspondence: Peter M Smith, Institute for Work & Health, 481 University Avenue, Suite 800, Toronto, Ontario, Canada M5G 2E9; Fax: (416) 927-4167; E-mail: psmith@iwh.on.ca

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