Health Physics Vol. 61, No. I (July), pp. 77-86, 1991 Printed in the U.S.A.
+
0017-9078/91 $3.00 .OO 0 1991 Health Physics Society Pergamon Press PIC
Paper OCULAR AND FACIAL SKIN EXPOSURE TO ULTRAVIOLET RADIATION IN SUNLIGHT A PERSONAL EXPOSURE MODEL WITH APPLICATION TO A WORKER POPULATION Frank S. Rosenthal School of Health Sciences, Purdue University, Civil Engineering Building, Room 1273, West Lafayette, IN 47907 and
Sheila K. West and Beatriz Munoz Johns Hopkins University, School of Medicine, Baltimore, MD 21205 and
Edward A. Emmett National Institute for Occupational Health and Safety, Sydney, Australia and
Paul T. Strickland Johns Hopkins University, School of Public Health, Baltimore, MD 2 1205 and
Hugh R. Taylor University of Melbourne, Melbourne, Australia
Abs?rw?-A model of ocular and facial skin exposure to UVB is presented that combines interview histories of work activities, leisure activities, eyeglass wearing, and hat use with field and laboratory measurements of UV radiant exposure. Site-specific exposure is expressed as the product of personal ambient exposure, defined as the ambient exposure while an individual is exposed to sunlight, and factors that describe the ratio of site-specific to personal ambient exposure. Ocular exposure is further corrected by the UV attenuation of typical eyewear. The model was used to compute cumulative and yearly exposures in a population of 838 watermen who work on the Chesapeake Bay and are highly exposed to sunlight. The model was found to be predictive of conditions known to be caused by excessive sun exposure-skin elastosis, climatic droplet keratopathy, and squamous cell carcinomaand has been useful in several epidemiological studies.
INTRODUCI'ION
tation of the corneal surface to incident radiation. The use of hat wear, spectacles, or sunglasses will result in a variable degree of UVR attenuation. Finally, a response spectrum must be chosen to weight the spectral distribution of incident light according to the biological effect of interest. Most of these considerations apply to skin exposure as well. Most previous studies have used surrogate variables such as latitude, sunlight hours, or ambient UVR measurements to estimate ocular or skin exposure. In this study, we have improved on these methods by developing a model of exposure that explicitly considers the factors described above. The model was developed for use in an epidemiological study of eye disease in a population of
EPIDEMIOLOGICAL studies of ultraviolet radiation (UVR) and eye disease are greatly strengthened when exposure of the subjects can be quantified. Ocular exposure to UVR depends on many factors. Place of residence and work determine ambient levels. Terrain and surface composition determine the amount of skylight and reflected light incidence at a given point. Patterns of work and leisure activities determine the time periods during which the subject is exposed. Type of activity will affect the orien(Manuscript received 2 July 1990; revised manuscript received 14 December 1990, accepted 20 December 1990) 77
78
Health Physics
838 watermen working on the Chesapeake Bay in Maryland state. This paper details the structure of the model, the measurements used to estimate the input parameters of the model, and its application to exposure assessment in the epidemiology study population.
MODEL
Dejinition of ocular exposure Ocular exposure (OE) is defined as the radiant exposure incident on a plane tangent to the cornea at its most anterior point. (See Appendix for a complete listing of abbreviations and symbols used in this paper.) The effective ocular exposure, OE,ff, is related to the spectral ocular exposure, OE( A), as follows: 0 E e= ~
R(A)OE( A)dA,
July I991, Volume 6 1, Number 1
of 69". Since most of the sun exposure in Maryland occurs between these values of solar altitude, the absolute value of 1 MSY is between 55 and 99 J cm-2. A more exact value could be computed based on solar altitude and ambient exposure in SBUs vs. hour throughout the year. However, an exact value was not needed for our work to proceed; thus we have not made this computation.
Structure of the model For a given year, effective ocular exposure (OE,ff)is computed as follows: 12
OE,ff=
C 2 PAE(A, M)FOE(A, M),
(2)
M=l A
where (1)
where R is a response spectrum that defines the spectral effectiveness of the radiation for the biological effect of interest. From eqn ( 1), OEeffclearly depends on the response spectrum chosen. In the initial development of our ocular exposure model, we assumed the response spectrum of the Robertson-Berger UVR meters that have been used extensively to make ambient measurements of UVR. This response spectrum has maximum response at the shortest wavelengths in sunlight and is close to an erythemal action spectrum (Berger 1976).
Definition of ambient exposure Ambient exposure is defined as the effective radiant exposure incident on a horizontal plane under an unobstructed sky. Total daily ambient exposure is the ambient exposure for all hours of a given day. Personal ambient exposure (PAE) is defined as the ambient exposure during the interval(s) of time while an individual is outdoors and exposed to sunlight. Exposure units The units of both ambient and effective ocular exposure are (effective energy) X area-', e.g., effective J cmP2.For convenience, we have also expressed exposure in units of the Maryland Sun Year (MSY), which we have defined to be the mean annual ambient exposure in Maryland where our epidemiological study occurred. The equivalence of the MSY in effective J cm-2 depends on the response spectrum chosen for the exposure assessment. The annual ambient exposure has been measured at various locations throughout the U.S. and the world with Robertson-Berger meters (Berger 1976). The output of these meters is in Sun Bum Units (SBUs). From data obtained by Scotto et al. ( 1977),a typical value for Maryland is estimated as 2,750 SBUs y-' . DeLuisi and Harris ( 1983) have determined the absolute effective energy of an SBU with respect to a standard erythemal action spectrum. They found that 1 SBU = 20 mJ cmP2at a solar altitude of 30" and 1 SBU = 36 mJ cmP2at a solar altitude
A = specified activity; M = month of the year; PAE(A, M) = monthly personal ambient exposure for a subject performing activity A in month M; FOE (A, M) = ratio of effective ocular exposure to personal ambient exposure for a subject performing activity A in month M . The determination of PAE and FOE is described further.
Determination of personal ambient exposure ( PAE) Monthly PAE (in MSYs) while performing activity A during month M is computed from the formula: PAE(A, M) = MAE(M) X DFAE(A, M)
x [ w w / 7 1 x LFW,
(3)
where MAE(M) = monthly ambient exposure (i.e., ambient exposure during month M in Maryland, in MSYs); DFAE(A , M) = daily fraction of ambient exposure (i.e., ratio of ambient exposure during the hours in which the activity is performed to daily ambient exposure); Table 1 . Monthly ambient exposure to UVB in Maryland. Month
Ambient exposure (MSY)
1 2 3
0.020 0.033 0.059
4
0.104
5 6
0.139 0.132
7 8
0.174
9 10 11 12
0.135 0.095 0.063 0.032 0.016
Ocular and skin UV exposure 0 F. S. ROSENTHAL et al.
79
Table 2. Mean fraction of total ambient UVB exposure occumng in a 1-h period of the day during specified months.
400
500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0.0 0.0 0.0 0.1 2.2 7.5 17.8 19.5 20.0 17.0 10.5 4.6 0.8 0.0 0.0 0.0
0.0 0.0 0.0 0.5 2.9 7.8 14.1 18.5 19.2 16.5 12.0 6.3 1.8 0.2 0.0 0.0
0.0 0.0 0.1 1.2 4.4 9.2 14.1 16.8 18.1 16.1 11.2 6.1 2.2 0.3 0.0 0.0
0.0 0.1 0.7 2.7 6.2 10.6 14.0 15.8 15.7 14.4 10.5 5.9 2.8 0.7 0.1 0.0
0.0 0.2 1.1 3.4 6.9 11.1 14.0 14.9 14.8 12.8 10.0 6.4 3.2 1.1 0.2 0.0
0.0 0.3 1.3 3.7 7.1 10.8 13.9 14.8 14.8 12.9 9.3 5.9 3.4 1.4 0.3 0.0
0.0 0.2 1.2 3.3 6.6 10.4 13.7 15.6 15.0 12.6 9.7 6.5 3.5 1.4 0.3 0.0
0.0 0.1 0.7 2.7 6.3 10.3 14.6 16.2 16.2 13.6 9.3 5.7 3.1 1.0 0.1 0.0
0.0 0.0 0.5 2.3 6.1 11.5 15.6 17.2 18.9 12.7 8.8 4.1 1.9 0.4 0.0 0.0
0.0 0.0 0.2 1.9 6.1 12.4 17.3 18.4 17.5 13.2 8.3 3.7 0.8 0.0 0.0 0.0
0.0 0.0 0.0 1.0 5.0 11.6 17.9 20.8 19.6 13.9 ,1.4 2.6 0.3 0.0 0.0 0.0
0.0 0.0 0.0 0.4 3.3 10.0 17.3 21.1 20.1 15.5 9.3 2.8 0.2 0.0 0.0 0.0
W(A) = days per week that a given activity is performed; LF(_4)= 1 for activities performed in Maryland = ratio of daily ambient exposure at the location in which the activity is performed to daily exposure in Maryland.
Other than dependencies indicated in parentheses, the quantities MAE, DFAE, W, and LF are assumed constant. The values of MAE(M) were obtained from Scotto et al. ( 1977), which give monthly UVB counts measured with Robertson-Berger meters at various U S . cities in 1975. Because counts were not available for Maryland, data from Philadelphia were used as approximations in computing MAE(M). The following formula was used to compute MAE (M) in MSY: MAE(M) = total counts during month M / total annual counts. ( 4 ) The values of MAE(M) computed from eqn (4)are shown in Table 1. The values of DFAE(A , M) were computed from the following formula:
As an approximation, values of HAE(H, M) measured in Philadelphia in 1974 (Scotto et al. 1977) were used. Values HAF(H, M) computed from these values of HAE(H, M) are shown in Table 2. Values of AI(A, H) are obtained from work and leisure histories obtained from a given subject through interviews, diaries, or questionnaires. Values of W(A) were obtained from the work and leisure histories. Values of LF were determined as follows: It was assumed that the ratio of total daily ambient exposure between a given location and Maryland was approximately equal to the ratio of annual exposures. Thus, LF = mean annual exposure in location where activity A was performed / mean annual exposure in Maryland. Values of LF for each of the 50 states and for selected locations worldwide were computed using ambient UVB maps developed by the National Oceanographic and Atmospheric Agency.* These maps are based on interpolation of data obtained with Robertson-Berger meters at selected locations in the U.S. Values of LF are tabulated in Table 3.
Determination of FOE(A, M ) FOE was computed as the product of two factors:
24
FOE(A, M) = Fl(A, M) X F2(A),
AI(A, H)HAF(A, M), ( 5 )
DFAE(A, M) =
(6)
where
H= 1
where A1 = activity index = 1 if the activity A is performed during hour H = 0, in all other cases; HAF( H , M) = hourly ambient fraction 24
= HAE(H, M ) /
C
HAE(H, M);
F1 (A, M) = ratio of effective ocular exposure to personal ambient exposure for a subject not wearing spectacles or sunglasses while performing activity A in month M, F2 (A ) = the attenuation of effective ocular exposure due to spectacles or sunglasses for activity A .
H= I
HAE(H, M) = hourly ambient exposure (i.e., mean ambient exposure during hour H in month M).
* Personal communication (November 1985), Dr. Gerald Cotton, Scientist,National Oceanographic and Atmospheric Agency, Washington, D.C.
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Health Physics
July 1991, Volume 61, Number 1
Table 3. Values of location factor (LF). ~~
~~
AL 1.3 AK 0.3 A 2 1.7 AR 1.2 CA 1.6 CO 1.4 CT 0.9 DE 0.9 DC 1.0 FL 1.6 =
Code: AF Europe, DK
GA I .3 HW 1.o I .2 ID IL 1.o IN 1.o IA 1.o 1.3 KS KY 1.o 1.3 LA ME 0.8 = Africa, AS = = do not know.
M D 1.o MA 0.9
MI
1.3
MN 0.8 MS 1.3 MO 1.1 MT 1.o NB 1.2 N V 1.6 NH 0.8 Asia, SA
=
South America, CB
The determination of F 1( A , M ) and F2 ( A) are described further.
Determination of F1 ( A , M ) The value of F1 ( A , M ) was based on experimental measurements made of the ocular exposure of outdoor workers, with and without hats, working in either summer (May through September) or non-summer (October through April) months, and working over either water or land surfaces (Table 4). A detailed account of the methods and results of these measurements are given elsewhere (Rosenthal et al. 1988). Briefly, workers wore a sampling badge consisting of UVR-sensitive polysulfone film on the bridge of spectacles, sunglasses, or eyeglass frames that they wore during their entire work period. Simultaneously, ambient levels were measured by exposing polysulfone film in a nearby field. A short questionnaire obtained at the end of the day was used to compute each subject’s PAE from the ambient measurements. From these measurements, F1 for each subject on a given day was determined as the ratio of ocular exposure to personal ambient exposure. The response spectrum of polysulfone film is similar to the Robertson-Berger response spectrum; however, its response drops off more gradually with wavelength (Davis et al. 198 1). Ideally, F 1 should be determined with the Table 4. F1 exposure matrix. Work over water
Use of brimmed hat
Season Summer Non-summer
No
Yes
0.074 0.172
0.045 0.097
Work over land Use of brimmed hat
Season Summer Non-Summer
No
Yes
0.046 0.046
0.020 0.020
1.o NJ NM I .7 NY 0.9 NC 1.2 N D 0.9 OH 0.9 OK 1.3 OR 0.9 PA 0.9 PR 2.2 =
RI
sc
sc
0.9 1.3 1
.o
TN 1.1 TX 1.4 UT 1.5 VT 0.8 VA 1.1 WA 0.9
wv
Caribbean, PC
WI WY EU PC CB SA AS AF DK
0.8 1.3 0.6 2.3 2.2 2.2 2.5 1.4
I .o
0.9 =
Pacific Islands, EU
same response spectrum as that used to determine PAE, i.e., the response spectrum of the Robertson-Berger meter. However, a suitable measurement medium was not available for this purpose. The value of F1 is independent of response spectrum only if the relative spectral distribution of light reaching the eye is the same as the relative ambient spectral distribution. Since this is not strictly true due to, for example, the contribution of ground reflected light to ocular exposure, some dependence of F1 on response spectrum may be expected. In a previous study with mannequins, it was found that values of F1 determined with polysulfone film were approximately 30%larger than those determined with Robertson-Berger meters ( Rosenthal et al. 1985). For the application of our exposure model to epidemiological studies, we were primarily interested in relative exposures (between subjects) rather than the absolute exposure for each subject. Therefore, it was considered that the values of F l relative to a Robertson-Berger response spectrum were sufficiently approximated by field measurements made with polysulfone film. Values of F1 were determined for both watermen and landscape workers. In both groups, wearing a brimmed hat significantly reduced ocular exposure. Exposure was greater in watermen than gardeners. For watermen, an almost two to one increase in the fraction of ambient exposure reaching the eyes in “non-summer” vs. summer months was observed (Rosenthal et al. 1988). Although we could not definitively identify the source of this difference, it was likely due to either differences in behavior of the watermen or differences in the spectral distribution of sunlight. In non-summer months, watermen performed oystering; in summer months, watermen performed crabbing. These activities involve somewhat different work tasks and equipment. In addition, there may have been a greater tendency to avoid exposure in the summer months due to higher ambient temperatures. We assumed that most land jobs were performed over grass or other relatively poorly reflecting terrain. We further assumed that F1 for land jobs was the same during non-summer months as during summer months, although we did not measure it during non-summer months. The data were grouped to determine F1 as a function of hat wear, season, and working surface. The values of F l derived from this data formed a 2 X 2 X 2 matrix shown in Table 4.
Ocular and skin UV exposure 0 F. S. ROSENTHALet al.
In practice, workers do not always wear their hats on a given day, and on some days may not wear them at all. Therefore, in the model, F1 (A, M) for a given subject was computed as a weighted average of its values for both hat wearing and non-wearing conditions; i.e., Fl (A, M) = F h ( A ) X F1 (hat, season, surface)
+ 11 - Fh(A)] X F l ( n o hat, season, surface),
(7)
where Fh(A) = the fraction of the time the subject wears a brimmed hat while performing activity A; season = summer, if M is between May and September = non-summer, if M is between October and April; surface = water, if activity A is performed over a water surface = land, if activity A is performed over a land surface. The values of F1 of the right side of eqn (7)are taken from the F1 exposure matrix (Table 4). The values of F h ( A ) were obtained from the work and leisure histories. F h ( A ) was scored on a five-category scale (never worn = 0; worn less than half the time = 0.25; worn half the time = 0.5; worn more than half the time = 0.75;worn all the time = 1 .O). The computation of F l ( A , M) from eqn (7)is illustrated by the following example: For a subject wearing a hat 75% of the time during the month of July while performing a job over a water surface, Fl(A, M) = (0.75)(0.045) (0.25)(0.074) = 0.052. No measurements of F1 for leisure activities were performed. It was assumed that F1 for leisure activities was equal to the value of F1 for work over a land surface. Discussion with individual watermen suggested that because of the great amount of working time that they spent over water, their leisure time was usually not spent over water.
+
Determination of F2(A) The factor F2 is given by:
F2(A) = Fe(A) X P
+ [l - Fe(A)] X 1.0,
(8)
where Fe(A) = the fraction of time the subject wears eyewear while performing activity A; P = the ratio of ocular exposure with eyewear to the ocular exposure when no eyewear is worn. The values of Fe are obtained from work and leisure histories. Values of P for typical eyewear were obtained from laboratory measurements using mannequin headforms without hats (Rosenthal et al. 1986). Ocular exposure and ambient exposure were using a UV radiometer with a wavelength response similar to that of the Robertson-Berger ambient UV monitors (Berger 1976). P was determined as the ratio of ocular exposure with the man-
81
nequin “wearing” the spectacles to the ocular exposure without the spectacles. Sixteen pairs of spectacles with glass lenses and 27 pairs of spectacles with plastic lenses were evaluated. The values of P obtained were: 0.067 k 0.007 (mean k SE) for spectacles with plastic lenses and 0.205 k 0.026 for spectacles with glass lenses. For use in the model computations, these were rounded off to 0.07 and 0.21, respectively. Further details on the determination of P are given by Rosenthal et al. ( 1986). The use of eqn (8) is illustrated by the following example: Assume a subject performs activity A , in which eyewear with plastic lenses is worn 80% of the time. Then F2(A) = (0.80)(0.07) (0.20)( 1.0) = 0.26.
+
Estimate of facial skin exposure Although the main emphasis of the development of the model was to provide estimates of ocular exposure, we also made modifications to the model for estimation of exposure to facial skin. To make this estimation, eqn (2 ) was replaced by: 12
FE,K=
2 2 PAE(A, M)FOE(A, M ) , M=l
(9)
A
where FE,r = annual effective facial skin exposure; A = specified activity; M = month of the year; PAE (A, M) = personal ambient exposure for a subject performing activity A in month M,. FSE(A, M) = ratio of effective facial skin exposure to personal ambient exposure for a subject performing activity A in month M. PAE was computed as before. To estimate FSE, we assumed that facial skin exposure was approximately equal to ocular exposure for a subject not wearing a hat or spectacles; i.e., FSE(A, M) = F l ( n o hat, season, surface).
(10)
Diffey et al. ( 1979)has shown that the UV exposure of facial skin varies greatly with anatomical site. Thus, our estimate of skin exposure must be considered approximate. A previous study found that, for mannequins without hats, the ratio of exposure on a few skin sites to ocular exposure ranged from 0.9-1.4, with a mean of 1.2 (Rosenthal et al. 1988). Thus, for subjects without hats or glasses, or to sites uninfluenced by hats or glasses, the skin exposure is likely to be underestimated by eqn ( 1 1 ). On the other hand, eqn ( 1 1 ) may overestimate exposure to facial skin sites that are shielded by hats or glasses. As with ocular exposure, it was assumed that the values of FSE did not depend on response spectrum.
APPLICATION TO AN OUTDOOR WORKER POPULATION The personal exposure model was applied to a population of Chesapeake Bay watermen who were the sub-
Health Physics
82
jects of an epidemiological study of long-term sunlight exposure and eye disease (Taylor et al. 1988). The population consisted of 838 men over the age of 30 y who resided in either Somerset County or lower Dorchester County and who had held at least one type of professional waterman license within the last 10 y. An exposure history was obtained through an interview with each subject, including a detailed occupational history covering each year of life from the age of 16 y, and a similar history for leisure activities. Both histories included information about hours spent outside, days per week for each activity, wearing of brimmed hats, and wearing of spectacles or sunglasses. For activities that were seasonal, information was obtained on a month-by-month basis. For each subject, the following quantities were computed from the exposure model: yearly ocular exposure for each year of life, mean annual ocular exposure, cumulative lifetime ocular exposure, personal ambient exposure, and facial skin exposure. Each subject in the study received a detailed skin and eye examination. The computed exposureswere used to examine exposure response relationships for a variety of health outcomes (Taylor et al. 1988; West et al. 1989; Taylor et al. 1989; Strickland et al. 1989; Cameron et al. 1988; Vitasa et al. 1990). The location of neoplastic and non-neoplastic skin lesions was determined for both existing and past lesions. Clinical diagnoses of squamous cell carcinoma and basal cell carcinoma were confirmed by histopathologic examination of biopsy material when it was available; diagnoses of previously removed lesions were verified from original pathology reports (Vitasa et al. 1990). The presence of elastosis of the facial skin was determined as described previously (Cameron et al. 1988). Four photographic slides of each subject's facial skin were obtained. Two physicians familiar with rating methodology rated these photographs according to a five-point scale: none, minor, moderate, moderately severe, and severe. Differences were settled by a third rater who was an experienced dermatologist. Each subject had an ocular examination that included a slit-lamp examination of the cornea. Climatic droplet keratopathy (CDK) was diagnosed when the characteristic gray droplets could be seen on retroillumination in the superficial corneal stroma with a clear zone separatingthem from the limbus (Taylor et al. 1989). Since both skin cancer and CDK have been associated with chronic UV exposure (Urbach 1984; Klintworth 1977), their relationship to dose estimates was examined using the exposure model. RESULTS Exposure histories for the subjects confirmed that in general they were highly exposed to sunlight. Sixty-four percent of the population were employed as watermen as their main job during their working lifetime; 18% were employed in various other outdoor jobs; 18%worked primarily in indoor jobs. For all workers, the average time
July 1991, Volume 61, Number 1
spent outdoors at work was 8.1 h d-'; the average time spent outdoors during days off was 4.9 h per day. Figure 1 shows histograms of personal ambient, facial, and ocular exposures. The distribution of ocular exposures is more skewed toward lower exposures compared to either personal ambient or facial exposure. This is likely due to the strong effect of spectacles in attenuating ocular exposure. The effect of spectacles is also evident in the bimodal distribution of UVB yearly exposures (Fig. 2). Thus, the peak at lower exposures is due to years in which subjects wore spectacles, whereas, the peak at higher exposures is due to years in which subjects did not wear spectacles. A multiple logistic regression of CDK prevalence vs. log cumulative ocular UVB exposure and age yielded a highly significant relationship for both the log of cumulative ocular exposure and age (p = 0.000 1 ), as reported previously. When the study population was stratified by age, those subjects with CDK had higher exposure in each decade. This difference was statistically significant for decades starting with age 50 (Fig. 3). The results also held true when a multiple logistic regression of CDK prevalence vs. log cumulative exposure and age was performed within each decade. To analyze the relationship of skin elastosis to cumulative facial skin exposure, subjects were grouped in two categories: Those with initial elastosisgrades of none, minor, or moderate were assigned a code of zero, while those with moderately severe or severe were assigned a code of one. A multiple logistic regression of skin elastosis code vs. log cumulative facial skin exposure and age yielded a highly significant relationship for both age (p = 0.0001) and the log of cumulative exposure (p = 0.0005) (see Table 5). When the data were stratified by age, the relationship between log cumulative exposure and elastosis was significant only for the youngest age group.
DISCUSSION The estimation of ocular and skin exposure to ultraviolet light is of considerable importance in studying the health effects of ultraviolet radiation. Rather than rely on surrogate variables as has been done in the past, the model presented here computes anatomic site-specific effective exposures. Because of the many factors involved in personal exposure, this computation depends on a synthesis of climatological information and personal behavior as revealed by interviews and questionnaires. The model is completed by experimental determinations of the following: 1) the relationship of site-specific to ambient exposure as a function of season, working surface, and wearing a brimmed hat; and 2) the effect of eyewear on ocular exposure. The model was found to be applicable to the epidemiological study population for which it was developed. Using ocular exposure estimates generated by the model, we have previously reported significant associations between exposure to UVB and the following eye conditions:
Ocular and skin UV exposure 0 F. S. ROSENTHAL et al.
83
80 C 0
60
,m
L
40
20 0
2
0
4
6
6
10
Average annual perronol ambient exposure (MSY x
0
1O-l)
2 4 Average annual UVB face exposure
6
(MSY x 10-2)
1251 r * 100 0 0) C
g
75
t
L.
50 25
LLA 6
0
2
0
0
Average annual UVB ocular exposure (MSY x 1 0-2)
Fig. 1. Distribution of average annual personal ambient, facial skin, and ocular UV exposure in a population of 838 watermen.
cortical cataracts (Taylor et al. 1988), CDK, pinguecula, and pyterigium (Taylor et al. 1989). We have also found significant associations with squamous cell carcinoma (Strickland et al. 1989). In this paper, we have shown a significant association between facial skin exposure to UVB and skin elastosis. These associations all provide support for the validity of the model. The usefulness of this model is further illustrated by our previous analysis of squamous cell carcinoma (SCC), basal cell carcinoma (BCC) , and actinic keratosis ( AK) in the watermen population (Strickland et al. 1989). In this analysis, personal exposure estimated by the model in MSY was converted to minimal erythema1 doses
(MED) using the relationship 1 MSY = 3260 MED. The prevalence of SCC, BCC, and AK for 30 MED intervals of exposure is shown in Fig. 4. This study confirmed previous estimates of the relationship of SCC to UV exposure. In addition, other features of the dose-response relationship were revealed: 1 ) Although both BCC and AK had a substantially higher prevalence than found in less-exposed populations, there was little correlation between prevalence and UV exposure in this population (Fig. 4). This phenomenon was attributed to a saturation effect at 0.4
& I
v
T
0.0-
I
I
2 a
i
0.2.-
-0.2.-
-0.4
I
z
(JI
3
?
P P
?
P
-0.6
2
T
i
1 1
-0.8 --
-1.0 -1.0--
0 Normal
0 0
COK
-1.2 -1.2.-
30-39
40-49
50-59
60-69
70-79
Age groups
2
4
6
a
Yearly UVB ocular exposure (MSY x
10
12
10-2)
Fig. 2. Distribution of yearly ocular exposures in a population of 838 watermen.
Fig. 3. Log cumulative ocular exposure in subjects with and without climatic droplet keratopathy (CDK), stratified by age. Error bars indicate the standard error of the mean in each group.
84
Health Physics
Table 5 . Multiple logistic regression of skin elastosis (EL) vs. age and log cumulative facial skin exposure to UVB (LGCUMEXP). Elastosis code: none, minor, moderate-EL = 0; moderately severe, severe-EL = 1. N
EL
Age
30-39 40-49 50-59 60-69 70+
=
0
LGCUMEXP
EL
=
40 61
152
16 40 46 32
1
Age
p
Std
Beta
Beta
1.906 0.657 0.004
NS
Std
p
NS’
0.130 0.067 0.052
118 115
0.601
NS
NS NS
88
NS
NS
0.335
0.073
Not significant (p > 0.10).
the high exposure levels experienced in the watermen population. In addition, there was evidence that some individuals were hypersusceptible to skin cancer: The group with lowest average annual exposure had a relatively high prevalence of SCC (6.3%) consisting of four cases (solid triangle in Fig. 4). In addition, five individuals were found with five or more SCCs and/or BCCs despite exposures that were average for the population. These features are not readily apparent in studies using surrogate measures of exposure, such as latitude of residence; because in such studies, individuals receiving a wide range of exposures are lumped together, obscuring effects related to very high or very low exposures. In con-
A
loo! 0
n
n
July 1991, Volume 61, Number 1
trast, by estimating individual personal exposures we were able to discern details of the exposure response relationship not otherwise obtainable. The relationship of facial skin exposure computed by the model and skin elastosis is also informative. The somewhat weaker relationship, as compared to CDK, may be explained by factors such as the dependence of elastosis on skin pigmentation, tanning ability, and the subjective nature of elastosis grading. In addition, the relationship between elastosis and exposure apparently gets weaker with age (Table 5 ). This may be due to a saturation effect in this highly exposed population: 73% of all subjects age 50 or older had severe grades of elastosis. Relative differences in exposure between these subjects weakens the association between exposure and elastosis in the overall logistic regression model. There is considerable room for further development and validation of this model. In particular, we were not able to examine the values of F1 in as wide a range of occupations as we would like; therefore, we do not know what degree of variability exists in this factor. Seasonal variations in this factor also need further investigation, as do factors affecting site-specific skin exposures. Exposure during leisure activities needs to be further explored. Although we felt that, in our population, the assumption that exposure during leisure activities was equivalent to work over a land surface of low reflectivity was reasonable, this may not be true in other populations. Leisure expo-
A 4
0
loo!
-T77-0
A 0
A
-I 1 1
1
I
I
1
I I l l 1
I
1
1
0 0
1
10 100 Average annual UV (MED year-
’>
10 100 Average a n n u a l UV (MED y e a r - ’ )
Fig. 4. Relationship of prevalence of skin neoplasms to individual average annual exposure to UVB radiation. Prevalence for actinic keratosis (0),squamous cell carcinoma ( A), and basal cell carcinoma ( 0 )was determined for 30-MED intervals of average annual exposure (e.g.,
+
0017-9078/91 $3.00 .OO 0 1991 Health Physics Society Pergamon Press PIC
Paper OCULAR AND FACIAL SKIN EXPOSURE TO ULTRAVIOLET RADIATION IN SUNLIGHT A PERSONAL EXPOSURE MODEL WITH APPLICATION TO A WORKER POPULATION Frank S. Rosenthal School of Health Sciences, Purdue University, Civil Engineering Building, Room 1273, West Lafayette, IN 47907 and
Sheila K. West and Beatriz Munoz Johns Hopkins University, School of Medicine, Baltimore, MD 21205 and
Edward A. Emmett National Institute for Occupational Health and Safety, Sydney, Australia and
Paul T. Strickland Johns Hopkins University, School of Public Health, Baltimore, MD 2 1205 and
Hugh R. Taylor University of Melbourne, Melbourne, Australia
Abs?rw?-A model of ocular and facial skin exposure to UVB is presented that combines interview histories of work activities, leisure activities, eyeglass wearing, and hat use with field and laboratory measurements of UV radiant exposure. Site-specific exposure is expressed as the product of personal ambient exposure, defined as the ambient exposure while an individual is exposed to sunlight, and factors that describe the ratio of site-specific to personal ambient exposure. Ocular exposure is further corrected by the UV attenuation of typical eyewear. The model was used to compute cumulative and yearly exposures in a population of 838 watermen who work on the Chesapeake Bay and are highly exposed to sunlight. The model was found to be predictive of conditions known to be caused by excessive sun exposure-skin elastosis, climatic droplet keratopathy, and squamous cell carcinomaand has been useful in several epidemiological studies.
INTRODUCI'ION
tation of the corneal surface to incident radiation. The use of hat wear, spectacles, or sunglasses will result in a variable degree of UVR attenuation. Finally, a response spectrum must be chosen to weight the spectral distribution of incident light according to the biological effect of interest. Most of these considerations apply to skin exposure as well. Most previous studies have used surrogate variables such as latitude, sunlight hours, or ambient UVR measurements to estimate ocular or skin exposure. In this study, we have improved on these methods by developing a model of exposure that explicitly considers the factors described above. The model was developed for use in an epidemiological study of eye disease in a population of
EPIDEMIOLOGICAL studies of ultraviolet radiation (UVR) and eye disease are greatly strengthened when exposure of the subjects can be quantified. Ocular exposure to UVR depends on many factors. Place of residence and work determine ambient levels. Terrain and surface composition determine the amount of skylight and reflected light incidence at a given point. Patterns of work and leisure activities determine the time periods during which the subject is exposed. Type of activity will affect the orien(Manuscript received 2 July 1990; revised manuscript received 14 December 1990, accepted 20 December 1990) 77
78
Health Physics
838 watermen working on the Chesapeake Bay in Maryland state. This paper details the structure of the model, the measurements used to estimate the input parameters of the model, and its application to exposure assessment in the epidemiology study population.
MODEL
Dejinition of ocular exposure Ocular exposure (OE) is defined as the radiant exposure incident on a plane tangent to the cornea at its most anterior point. (See Appendix for a complete listing of abbreviations and symbols used in this paper.) The effective ocular exposure, OE,ff, is related to the spectral ocular exposure, OE( A), as follows: 0 E e= ~
R(A)OE( A)dA,
July I991, Volume 6 1, Number 1
of 69". Since most of the sun exposure in Maryland occurs between these values of solar altitude, the absolute value of 1 MSY is between 55 and 99 J cm-2. A more exact value could be computed based on solar altitude and ambient exposure in SBUs vs. hour throughout the year. However, an exact value was not needed for our work to proceed; thus we have not made this computation.
Structure of the model For a given year, effective ocular exposure (OE,ff)is computed as follows: 12
OE,ff=
C 2 PAE(A, M)FOE(A, M),
(2)
M=l A
where (1)
where R is a response spectrum that defines the spectral effectiveness of the radiation for the biological effect of interest. From eqn ( 1), OEeffclearly depends on the response spectrum chosen. In the initial development of our ocular exposure model, we assumed the response spectrum of the Robertson-Berger UVR meters that have been used extensively to make ambient measurements of UVR. This response spectrum has maximum response at the shortest wavelengths in sunlight and is close to an erythemal action spectrum (Berger 1976).
Definition of ambient exposure Ambient exposure is defined as the effective radiant exposure incident on a horizontal plane under an unobstructed sky. Total daily ambient exposure is the ambient exposure for all hours of a given day. Personal ambient exposure (PAE) is defined as the ambient exposure during the interval(s) of time while an individual is outdoors and exposed to sunlight. Exposure units The units of both ambient and effective ocular exposure are (effective energy) X area-', e.g., effective J cmP2.For convenience, we have also expressed exposure in units of the Maryland Sun Year (MSY), which we have defined to be the mean annual ambient exposure in Maryland where our epidemiological study occurred. The equivalence of the MSY in effective J cm-2 depends on the response spectrum chosen for the exposure assessment. The annual ambient exposure has been measured at various locations throughout the U.S. and the world with Robertson-Berger meters (Berger 1976). The output of these meters is in Sun Bum Units (SBUs). From data obtained by Scotto et al. ( 1977),a typical value for Maryland is estimated as 2,750 SBUs y-' . DeLuisi and Harris ( 1983) have determined the absolute effective energy of an SBU with respect to a standard erythemal action spectrum. They found that 1 SBU = 20 mJ cmP2at a solar altitude of 30" and 1 SBU = 36 mJ cmP2at a solar altitude
A = specified activity; M = month of the year; PAE(A, M) = monthly personal ambient exposure for a subject performing activity A in month M; FOE (A, M) = ratio of effective ocular exposure to personal ambient exposure for a subject performing activity A in month M . The determination of PAE and FOE is described further.
Determination of personal ambient exposure ( PAE) Monthly PAE (in MSYs) while performing activity A during month M is computed from the formula: PAE(A, M) = MAE(M) X DFAE(A, M)
x [ w w / 7 1 x LFW,
(3)
where MAE(M) = monthly ambient exposure (i.e., ambient exposure during month M in Maryland, in MSYs); DFAE(A , M) = daily fraction of ambient exposure (i.e., ratio of ambient exposure during the hours in which the activity is performed to daily ambient exposure); Table 1 . Monthly ambient exposure to UVB in Maryland. Month
Ambient exposure (MSY)
1 2 3
0.020 0.033 0.059
4
0.104
5 6
0.139 0.132
7 8
0.174
9 10 11 12
0.135 0.095 0.063 0.032 0.016
Ocular and skin UV exposure 0 F. S. ROSENTHAL et al.
79
Table 2. Mean fraction of total ambient UVB exposure occumng in a 1-h period of the day during specified months.
400
500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
0.0 0.0 0.0 0.1 2.2 7.5 17.8 19.5 20.0 17.0 10.5 4.6 0.8 0.0 0.0 0.0
0.0 0.0 0.0 0.5 2.9 7.8 14.1 18.5 19.2 16.5 12.0 6.3 1.8 0.2 0.0 0.0
0.0 0.0 0.1 1.2 4.4 9.2 14.1 16.8 18.1 16.1 11.2 6.1 2.2 0.3 0.0 0.0
0.0 0.1 0.7 2.7 6.2 10.6 14.0 15.8 15.7 14.4 10.5 5.9 2.8 0.7 0.1 0.0
0.0 0.2 1.1 3.4 6.9 11.1 14.0 14.9 14.8 12.8 10.0 6.4 3.2 1.1 0.2 0.0
0.0 0.3 1.3 3.7 7.1 10.8 13.9 14.8 14.8 12.9 9.3 5.9 3.4 1.4 0.3 0.0
0.0 0.2 1.2 3.3 6.6 10.4 13.7 15.6 15.0 12.6 9.7 6.5 3.5 1.4 0.3 0.0
0.0 0.1 0.7 2.7 6.3 10.3 14.6 16.2 16.2 13.6 9.3 5.7 3.1 1.0 0.1 0.0
0.0 0.0 0.5 2.3 6.1 11.5 15.6 17.2 18.9 12.7 8.8 4.1 1.9 0.4 0.0 0.0
0.0 0.0 0.2 1.9 6.1 12.4 17.3 18.4 17.5 13.2 8.3 3.7 0.8 0.0 0.0 0.0
0.0 0.0 0.0 1.0 5.0 11.6 17.9 20.8 19.6 13.9 ,1.4 2.6 0.3 0.0 0.0 0.0
0.0 0.0 0.0 0.4 3.3 10.0 17.3 21.1 20.1 15.5 9.3 2.8 0.2 0.0 0.0 0.0
W(A) = days per week that a given activity is performed; LF(_4)= 1 for activities performed in Maryland = ratio of daily ambient exposure at the location in which the activity is performed to daily exposure in Maryland.
Other than dependencies indicated in parentheses, the quantities MAE, DFAE, W, and LF are assumed constant. The values of MAE(M) were obtained from Scotto et al. ( 1977), which give monthly UVB counts measured with Robertson-Berger meters at various U S . cities in 1975. Because counts were not available for Maryland, data from Philadelphia were used as approximations in computing MAE(M). The following formula was used to compute MAE (M) in MSY: MAE(M) = total counts during month M / total annual counts. ( 4 ) The values of MAE(M) computed from eqn (4)are shown in Table 1. The values of DFAE(A , M) were computed from the following formula:
As an approximation, values of HAE(H, M) measured in Philadelphia in 1974 (Scotto et al. 1977) were used. Values HAF(H, M) computed from these values of HAE(H, M) are shown in Table 2. Values of AI(A, H) are obtained from work and leisure histories obtained from a given subject through interviews, diaries, or questionnaires. Values of W(A) were obtained from the work and leisure histories. Values of LF were determined as follows: It was assumed that the ratio of total daily ambient exposure between a given location and Maryland was approximately equal to the ratio of annual exposures. Thus, LF = mean annual exposure in location where activity A was performed / mean annual exposure in Maryland. Values of LF for each of the 50 states and for selected locations worldwide were computed using ambient UVB maps developed by the National Oceanographic and Atmospheric Agency.* These maps are based on interpolation of data obtained with Robertson-Berger meters at selected locations in the U.S. Values of LF are tabulated in Table 3.
Determination of FOE(A, M ) FOE was computed as the product of two factors:
24
FOE(A, M) = Fl(A, M) X F2(A),
AI(A, H)HAF(A, M), ( 5 )
DFAE(A, M) =
(6)
where
H= 1
where A1 = activity index = 1 if the activity A is performed during hour H = 0, in all other cases; HAF( H , M) = hourly ambient fraction 24
= HAE(H, M ) /
C
HAE(H, M);
F1 (A, M) = ratio of effective ocular exposure to personal ambient exposure for a subject not wearing spectacles or sunglasses while performing activity A in month M, F2 (A ) = the attenuation of effective ocular exposure due to spectacles or sunglasses for activity A .
H= I
HAE(H, M) = hourly ambient exposure (i.e., mean ambient exposure during hour H in month M).
* Personal communication (November 1985), Dr. Gerald Cotton, Scientist,National Oceanographic and Atmospheric Agency, Washington, D.C.
80
Health Physics
July 1991, Volume 61, Number 1
Table 3. Values of location factor (LF). ~~
~~
AL 1.3 AK 0.3 A 2 1.7 AR 1.2 CA 1.6 CO 1.4 CT 0.9 DE 0.9 DC 1.0 FL 1.6 =
Code: AF Europe, DK
GA I .3 HW 1.o I .2 ID IL 1.o IN 1.o IA 1.o 1.3 KS KY 1.o 1.3 LA ME 0.8 = Africa, AS = = do not know.
M D 1.o MA 0.9
MI
1.3
MN 0.8 MS 1.3 MO 1.1 MT 1.o NB 1.2 N V 1.6 NH 0.8 Asia, SA
=
South America, CB
The determination of F 1( A , M ) and F2 ( A) are described further.
Determination of F1 ( A , M ) The value of F1 ( A , M ) was based on experimental measurements made of the ocular exposure of outdoor workers, with and without hats, working in either summer (May through September) or non-summer (October through April) months, and working over either water or land surfaces (Table 4). A detailed account of the methods and results of these measurements are given elsewhere (Rosenthal et al. 1988). Briefly, workers wore a sampling badge consisting of UVR-sensitive polysulfone film on the bridge of spectacles, sunglasses, or eyeglass frames that they wore during their entire work period. Simultaneously, ambient levels were measured by exposing polysulfone film in a nearby field. A short questionnaire obtained at the end of the day was used to compute each subject’s PAE from the ambient measurements. From these measurements, F1 for each subject on a given day was determined as the ratio of ocular exposure to personal ambient exposure. The response spectrum of polysulfone film is similar to the Robertson-Berger response spectrum; however, its response drops off more gradually with wavelength (Davis et al. 198 1). Ideally, F 1 should be determined with the Table 4. F1 exposure matrix. Work over water
Use of brimmed hat
Season Summer Non-summer
No
Yes
0.074 0.172
0.045 0.097
Work over land Use of brimmed hat
Season Summer Non-Summer
No
Yes
0.046 0.046
0.020 0.020
1.o NJ NM I .7 NY 0.9 NC 1.2 N D 0.9 OH 0.9 OK 1.3 OR 0.9 PA 0.9 PR 2.2 =
RI
sc
sc
0.9 1.3 1
.o
TN 1.1 TX 1.4 UT 1.5 VT 0.8 VA 1.1 WA 0.9
wv
Caribbean, PC
WI WY EU PC CB SA AS AF DK
0.8 1.3 0.6 2.3 2.2 2.2 2.5 1.4
I .o
0.9 =
Pacific Islands, EU
same response spectrum as that used to determine PAE, i.e., the response spectrum of the Robertson-Berger meter. However, a suitable measurement medium was not available for this purpose. The value of F1 is independent of response spectrum only if the relative spectral distribution of light reaching the eye is the same as the relative ambient spectral distribution. Since this is not strictly true due to, for example, the contribution of ground reflected light to ocular exposure, some dependence of F1 on response spectrum may be expected. In a previous study with mannequins, it was found that values of F1 determined with polysulfone film were approximately 30%larger than those determined with Robertson-Berger meters ( Rosenthal et al. 1985). For the application of our exposure model to epidemiological studies, we were primarily interested in relative exposures (between subjects) rather than the absolute exposure for each subject. Therefore, it was considered that the values of F l relative to a Robertson-Berger response spectrum were sufficiently approximated by field measurements made with polysulfone film. Values of F1 were determined for both watermen and landscape workers. In both groups, wearing a brimmed hat significantly reduced ocular exposure. Exposure was greater in watermen than gardeners. For watermen, an almost two to one increase in the fraction of ambient exposure reaching the eyes in “non-summer” vs. summer months was observed (Rosenthal et al. 1988). Although we could not definitively identify the source of this difference, it was likely due to either differences in behavior of the watermen or differences in the spectral distribution of sunlight. In non-summer months, watermen performed oystering; in summer months, watermen performed crabbing. These activities involve somewhat different work tasks and equipment. In addition, there may have been a greater tendency to avoid exposure in the summer months due to higher ambient temperatures. We assumed that most land jobs were performed over grass or other relatively poorly reflecting terrain. We further assumed that F1 for land jobs was the same during non-summer months as during summer months, although we did not measure it during non-summer months. The data were grouped to determine F1 as a function of hat wear, season, and working surface. The values of F l derived from this data formed a 2 X 2 X 2 matrix shown in Table 4.
Ocular and skin UV exposure 0 F. S. ROSENTHALet al.
In practice, workers do not always wear their hats on a given day, and on some days may not wear them at all. Therefore, in the model, F1 (A, M) for a given subject was computed as a weighted average of its values for both hat wearing and non-wearing conditions; i.e., Fl (A, M) = F h ( A ) X F1 (hat, season, surface)
+ 11 - Fh(A)] X F l ( n o hat, season, surface),
(7)
where Fh(A) = the fraction of the time the subject wears a brimmed hat while performing activity A; season = summer, if M is between May and September = non-summer, if M is between October and April; surface = water, if activity A is performed over a water surface = land, if activity A is performed over a land surface. The values of F1 of the right side of eqn (7)are taken from the F1 exposure matrix (Table 4). The values of F h ( A ) were obtained from the work and leisure histories. F h ( A ) was scored on a five-category scale (never worn = 0; worn less than half the time = 0.25; worn half the time = 0.5; worn more than half the time = 0.75;worn all the time = 1 .O). The computation of F l ( A , M) from eqn (7)is illustrated by the following example: For a subject wearing a hat 75% of the time during the month of July while performing a job over a water surface, Fl(A, M) = (0.75)(0.045) (0.25)(0.074) = 0.052. No measurements of F1 for leisure activities were performed. It was assumed that F1 for leisure activities was equal to the value of F1 for work over a land surface. Discussion with individual watermen suggested that because of the great amount of working time that they spent over water, their leisure time was usually not spent over water.
+
Determination of F2(A) The factor F2 is given by:
F2(A) = Fe(A) X P
+ [l - Fe(A)] X 1.0,
(8)
where Fe(A) = the fraction of time the subject wears eyewear while performing activity A; P = the ratio of ocular exposure with eyewear to the ocular exposure when no eyewear is worn. The values of Fe are obtained from work and leisure histories. Values of P for typical eyewear were obtained from laboratory measurements using mannequin headforms without hats (Rosenthal et al. 1986). Ocular exposure and ambient exposure were using a UV radiometer with a wavelength response similar to that of the Robertson-Berger ambient UV monitors (Berger 1976). P was determined as the ratio of ocular exposure with the man-
81
nequin “wearing” the spectacles to the ocular exposure without the spectacles. Sixteen pairs of spectacles with glass lenses and 27 pairs of spectacles with plastic lenses were evaluated. The values of P obtained were: 0.067 k 0.007 (mean k SE) for spectacles with plastic lenses and 0.205 k 0.026 for spectacles with glass lenses. For use in the model computations, these were rounded off to 0.07 and 0.21, respectively. Further details on the determination of P are given by Rosenthal et al. ( 1986). The use of eqn (8) is illustrated by the following example: Assume a subject performs activity A , in which eyewear with plastic lenses is worn 80% of the time. Then F2(A) = (0.80)(0.07) (0.20)( 1.0) = 0.26.
+
Estimate of facial skin exposure Although the main emphasis of the development of the model was to provide estimates of ocular exposure, we also made modifications to the model for estimation of exposure to facial skin. To make this estimation, eqn (2 ) was replaced by: 12
FE,K=
2 2 PAE(A, M)FOE(A, M ) , M=l
(9)
A
where FE,r = annual effective facial skin exposure; A = specified activity; M = month of the year; PAE (A, M) = personal ambient exposure for a subject performing activity A in month M,. FSE(A, M) = ratio of effective facial skin exposure to personal ambient exposure for a subject performing activity A in month M. PAE was computed as before. To estimate FSE, we assumed that facial skin exposure was approximately equal to ocular exposure for a subject not wearing a hat or spectacles; i.e., FSE(A, M) = F l ( n o hat, season, surface).
(10)
Diffey et al. ( 1979)has shown that the UV exposure of facial skin varies greatly with anatomical site. Thus, our estimate of skin exposure must be considered approximate. A previous study found that, for mannequins without hats, the ratio of exposure on a few skin sites to ocular exposure ranged from 0.9-1.4, with a mean of 1.2 (Rosenthal et al. 1988). Thus, for subjects without hats or glasses, or to sites uninfluenced by hats or glasses, the skin exposure is likely to be underestimated by eqn ( 1 1 ). On the other hand, eqn ( 1 1 ) may overestimate exposure to facial skin sites that are shielded by hats or glasses. As with ocular exposure, it was assumed that the values of FSE did not depend on response spectrum.
APPLICATION TO AN OUTDOOR WORKER POPULATION The personal exposure model was applied to a population of Chesapeake Bay watermen who were the sub-
Health Physics
82
jects of an epidemiological study of long-term sunlight exposure and eye disease (Taylor et al. 1988). The population consisted of 838 men over the age of 30 y who resided in either Somerset County or lower Dorchester County and who had held at least one type of professional waterman license within the last 10 y. An exposure history was obtained through an interview with each subject, including a detailed occupational history covering each year of life from the age of 16 y, and a similar history for leisure activities. Both histories included information about hours spent outside, days per week for each activity, wearing of brimmed hats, and wearing of spectacles or sunglasses. For activities that were seasonal, information was obtained on a month-by-month basis. For each subject, the following quantities were computed from the exposure model: yearly ocular exposure for each year of life, mean annual ocular exposure, cumulative lifetime ocular exposure, personal ambient exposure, and facial skin exposure. Each subject in the study received a detailed skin and eye examination. The computed exposureswere used to examine exposure response relationships for a variety of health outcomes (Taylor et al. 1988; West et al. 1989; Taylor et al. 1989; Strickland et al. 1989; Cameron et al. 1988; Vitasa et al. 1990). The location of neoplastic and non-neoplastic skin lesions was determined for both existing and past lesions. Clinical diagnoses of squamous cell carcinoma and basal cell carcinoma were confirmed by histopathologic examination of biopsy material when it was available; diagnoses of previously removed lesions were verified from original pathology reports (Vitasa et al. 1990). The presence of elastosis of the facial skin was determined as described previously (Cameron et al. 1988). Four photographic slides of each subject's facial skin were obtained. Two physicians familiar with rating methodology rated these photographs according to a five-point scale: none, minor, moderate, moderately severe, and severe. Differences were settled by a third rater who was an experienced dermatologist. Each subject had an ocular examination that included a slit-lamp examination of the cornea. Climatic droplet keratopathy (CDK) was diagnosed when the characteristic gray droplets could be seen on retroillumination in the superficial corneal stroma with a clear zone separatingthem from the limbus (Taylor et al. 1989). Since both skin cancer and CDK have been associated with chronic UV exposure (Urbach 1984; Klintworth 1977), their relationship to dose estimates was examined using the exposure model. RESULTS Exposure histories for the subjects confirmed that in general they were highly exposed to sunlight. Sixty-four percent of the population were employed as watermen as their main job during their working lifetime; 18% were employed in various other outdoor jobs; 18%worked primarily in indoor jobs. For all workers, the average time
July 1991, Volume 61, Number 1
spent outdoors at work was 8.1 h d-'; the average time spent outdoors during days off was 4.9 h per day. Figure 1 shows histograms of personal ambient, facial, and ocular exposures. The distribution of ocular exposures is more skewed toward lower exposures compared to either personal ambient or facial exposure. This is likely due to the strong effect of spectacles in attenuating ocular exposure. The effect of spectacles is also evident in the bimodal distribution of UVB yearly exposures (Fig. 2). Thus, the peak at lower exposures is due to years in which subjects wore spectacles, whereas, the peak at higher exposures is due to years in which subjects did not wear spectacles. A multiple logistic regression of CDK prevalence vs. log cumulative ocular UVB exposure and age yielded a highly significant relationship for both the log of cumulative ocular exposure and age (p = 0.000 1 ), as reported previously. When the study population was stratified by age, those subjects with CDK had higher exposure in each decade. This difference was statistically significant for decades starting with age 50 (Fig. 3). The results also held true when a multiple logistic regression of CDK prevalence vs. log cumulative exposure and age was performed within each decade. To analyze the relationship of skin elastosis to cumulative facial skin exposure, subjects were grouped in two categories: Those with initial elastosisgrades of none, minor, or moderate were assigned a code of zero, while those with moderately severe or severe were assigned a code of one. A multiple logistic regression of skin elastosis code vs. log cumulative facial skin exposure and age yielded a highly significant relationship for both age (p = 0.0001) and the log of cumulative exposure (p = 0.0005) (see Table 5). When the data were stratified by age, the relationship between log cumulative exposure and elastosis was significant only for the youngest age group.
DISCUSSION The estimation of ocular and skin exposure to ultraviolet light is of considerable importance in studying the health effects of ultraviolet radiation. Rather than rely on surrogate variables as has been done in the past, the model presented here computes anatomic site-specific effective exposures. Because of the many factors involved in personal exposure, this computation depends on a synthesis of climatological information and personal behavior as revealed by interviews and questionnaires. The model is completed by experimental determinations of the following: 1) the relationship of site-specific to ambient exposure as a function of season, working surface, and wearing a brimmed hat; and 2) the effect of eyewear on ocular exposure. The model was found to be applicable to the epidemiological study population for which it was developed. Using ocular exposure estimates generated by the model, we have previously reported significant associations between exposure to UVB and the following eye conditions:
Ocular and skin UV exposure 0 F. S. ROSENTHAL et al.
83
80 C 0
60
,m
L
40
20 0
2
0
4
6
6
10
Average annual perronol ambient exposure (MSY x
0
1O-l)
2 4 Average annual UVB face exposure
6
(MSY x 10-2)
1251 r * 100 0 0) C
g
75
t
L.
50 25
LLA 6
0
2
0
0
Average annual UVB ocular exposure (MSY x 1 0-2)
Fig. 1. Distribution of average annual personal ambient, facial skin, and ocular UV exposure in a population of 838 watermen.
cortical cataracts (Taylor et al. 1988), CDK, pinguecula, and pyterigium (Taylor et al. 1989). We have also found significant associations with squamous cell carcinoma (Strickland et al. 1989). In this paper, we have shown a significant association between facial skin exposure to UVB and skin elastosis. These associations all provide support for the validity of the model. The usefulness of this model is further illustrated by our previous analysis of squamous cell carcinoma (SCC), basal cell carcinoma (BCC) , and actinic keratosis ( AK) in the watermen population (Strickland et al. 1989). In this analysis, personal exposure estimated by the model in MSY was converted to minimal erythema1 doses
(MED) using the relationship 1 MSY = 3260 MED. The prevalence of SCC, BCC, and AK for 30 MED intervals of exposure is shown in Fig. 4. This study confirmed previous estimates of the relationship of SCC to UV exposure. In addition, other features of the dose-response relationship were revealed: 1 ) Although both BCC and AK had a substantially higher prevalence than found in less-exposed populations, there was little correlation between prevalence and UV exposure in this population (Fig. 4). This phenomenon was attributed to a saturation effect at 0.4
& I
v
T
0.0-
I
I
2 a
i
0.2.-
-0.2.-
-0.4
I
z
(JI
3
?
P P
?
P
-0.6
2
T
i
1 1
-0.8 --
-1.0 -1.0--
0 Normal
0 0
COK
-1.2 -1.2.-
30-39
40-49
50-59
60-69
70-79
Age groups
2
4
6
a
Yearly UVB ocular exposure (MSY x
10
12
10-2)
Fig. 2. Distribution of yearly ocular exposures in a population of 838 watermen.
Fig. 3. Log cumulative ocular exposure in subjects with and without climatic droplet keratopathy (CDK), stratified by age. Error bars indicate the standard error of the mean in each group.
84
Health Physics
Table 5 . Multiple logistic regression of skin elastosis (EL) vs. age and log cumulative facial skin exposure to UVB (LGCUMEXP). Elastosis code: none, minor, moderate-EL = 0; moderately severe, severe-EL = 1. N
EL
Age
30-39 40-49 50-59 60-69 70+
=
0
LGCUMEXP
EL
=
40 61
152
16 40 46 32
1
Age
p
Std
Beta
Beta
1.906 0.657 0.004
NS
Std
p
NS’
0.130 0.067 0.052
118 115
0.601
NS
NS NS
88
NS
NS
0.335
0.073
Not significant (p > 0.10).
the high exposure levels experienced in the watermen population. In addition, there was evidence that some individuals were hypersusceptible to skin cancer: The group with lowest average annual exposure had a relatively high prevalence of SCC (6.3%) consisting of four cases (solid triangle in Fig. 4). In addition, five individuals were found with five or more SCCs and/or BCCs despite exposures that were average for the population. These features are not readily apparent in studies using surrogate measures of exposure, such as latitude of residence; because in such studies, individuals receiving a wide range of exposures are lumped together, obscuring effects related to very high or very low exposures. In con-
A
loo! 0
n
n
July 1991, Volume 61, Number 1
trast, by estimating individual personal exposures we were able to discern details of the exposure response relationship not otherwise obtainable. The relationship of facial skin exposure computed by the model and skin elastosis is also informative. The somewhat weaker relationship, as compared to CDK, may be explained by factors such as the dependence of elastosis on skin pigmentation, tanning ability, and the subjective nature of elastosis grading. In addition, the relationship between elastosis and exposure apparently gets weaker with age (Table 5 ). This may be due to a saturation effect in this highly exposed population: 73% of all subjects age 50 or older had severe grades of elastosis. Relative differences in exposure between these subjects weakens the association between exposure and elastosis in the overall logistic regression model. There is considerable room for further development and validation of this model. In particular, we were not able to examine the values of F1 in as wide a range of occupations as we would like; therefore, we do not know what degree of variability exists in this factor. Seasonal variations in this factor also need further investigation, as do factors affecting site-specific skin exposures. Exposure during leisure activities needs to be further explored. Although we felt that, in our population, the assumption that exposure during leisure activities was equivalent to work over a land surface of low reflectivity was reasonable, this may not be true in other populations. Leisure expo-
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Fig. 4. Relationship of prevalence of skin neoplasms to individual average annual exposure to UVB radiation. Prevalence for actinic keratosis (0),squamous cell carcinoma ( A), and basal cell carcinoma ( 0 )was determined for 30-MED intervals of average annual exposure (e.g.,
