Azaroff et al.1, raised the issue as to how much undercounting of
occupational injuries actually occur. They proposed a filtering system
for “catching” those that fall into this undercount. Undercounting has
always been a problem in counting studies in that one never knows how many
they really missed. The purpose of this filtering system is to collect
and count workers that were not identified on the original reporting.
This concept is an excellent idea but in-itself will not provide an
accurate count of all those that are reportable within a specific system,
facility or type of injury. So the filters primarily become different
lists of those being counted. However, this is an excellent way of
generating lists that can be used in the capture-recapture method (CRM) of
ascertaining the countable number of events2. Azaroff et al.1, does make
reference to one study3 in their paper that employed the CRM. Review of
the literature reveals that the CRM is not commonly used in injury
epidemiology, although its potential is enormous, however, its use is
growing.
The CRM has been effectively used to count wildlife populations for
decades4. This method employs multiple lists to identify the cases and
then uses the overlap information among the lists to estimate the total
number of cases5,6. The various filters that are illustrated in Figure 1
of Azaroff et al.1 paper can be potential sources for the capture-
recapture application to estimate the size of work-related injuries.
Each of the filters will have a different efficiency at capturing one
segment of the total capturable population of work related injuries. The
use of more than two listings will require employment of a CRM log-linear
model. The model with three listings is illustrated in Figure 1. Each
circle would represent a separate captured segment of the total population
that would be obtained from a filter. For example, one filter (Source 1)
would represent workers who lost more than 5 days. As indicated, some of
these workers would also be represented on a second filter (list) (Source
3) as population A and B. Employment of a simple model, as shown in the
Figure, the total ascertainable work related injury population could then
be estimated using this contingency table.
The number of events estimated by the CRM can be compared to OSHA
logs and workers’ compensation records. This will allow comparison for
the accuracy of these records and may provide clues to the best filters in
capturing injured workers under different events. By combining the
proposed filtering for occupational injuries and employment of the CRM
there will be a mechanism of potentially locating the best reporting
systems for ascertaining underreported injuries.
CRM provides an estimate of the number of cases that could have been
caught, and to be caught each person needs to have experienced a work
related injury. Employment of this methodology has been shown to be
effective in previous injury studies that did not use filters per se7,8.
This method will not capture those that were never detected by a filter.
It does, however, reduce the historical problem of counting in work
related injuries, that of ascertainment, and thus produces an
ascertainment corrected estimate. The CRM estimate, although not perfect,
is most certainly much closer to the truth for methods of counting than
for methods that do not control for ascertainment.
Many investigators view missing cases of injuries or disease as part
of the error measurement, a mistake, sloppiness of the study or just a
“sin”. There needs to be a better understanding of the concept of missing
cases9 in that they are an “ERROR” and to recognize that when counting
populations there will inherently be missed cases. Thus, the “sin” is not
missing cases, but instead is not using an appropriate statistical
methodology for determining the degree of ascertainment and adjusting for
the ascertaiment corrected incidence rates. The CRM is not limited to
injury studies or epidemiology, but can be applied effectively in other
fields as well10, so why not apply an old method to new problems.
References
1. Azaroff LS, Levenstein C, Wegman DH. 2003. Occupational injury and
illness surveillance: conceptual filters explain underreporting. Am J
Public Health. 2002; 92: 1421-9.
2. McCarty DJ, Tull ES, Moy CS, Kwoh CK, LaPorte RE. Ascertainment
corrected rates: applications of the capture-recapture methods. Int J
Epidemiol. 1993; 22: 559-65.
3. Morse T, Dillon C, Warren N, Hall C, Hovey D. Capture-recapture
estimation of unreported work-related musculoskeletal disorders in
Connecticut. Am J Ind Med 2001; 39: 636-42.
4. LaPorte RE, McCarty DJ, Tull ES, Tajima N. 1992. County birds,
bees and NCDs. Lancet 339: 494-5.
5. International Working Group for Disease Monitoring and
Forecasting.
Capture-recapture and multiple-record systems estimation, I. History and
Theoretical development. Am J Epidemiology 1995;142-1047-58.
6. International Working Group for Disease Monitoring and
Forecasting.
Capture-recapture and multiple-record systems estimation,II. Application
to human diseases. Am J Epidemiology 1995;142:1059-68.
7. Chiu W-T, Dearwater SR, McCarty DJ, Songer TJ, LaPorte RE. 1993.
Establishment of accurate incidence rates for head and spinal cord
injuries in developing and developed countries: a capture-recapture
approach. J Trama. 35: 206-11.
8. Surkin J, Smith M, Penman A, Currier M, Harkey HL, Chang YF.
Spinal cord injury incidence in Mississippi: A capture-recapture approach.
J Trama 1998;45:502-504.
9. LaPorte RE. Assessing the human condition: capture-recapture
techniques – allows accurate count of those difficult to reach
populations. Lancet 1993; 308: 5-6.
10. Lange JH, LaPorte RE, Chang Y-F Exposure to lead and an old way
of counting. Environ Health Perspectives (Letter) 2003; (accepted).
Total size of the
actual number of cases
(unknown)
This unknown is cases not
Identified by any of the lists
Source 3
Present Absent
Source 2 Source 2
Present Absent Present Absent
Present A B E F
Source 1
Absent C D G ?
Figure 1. Three-source combinations for estimating the number of
actual cases