a Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Canada.
b Menzies Centre for Population Health Research, University of Tasmania, Hobart, Tasmania, Australia.
c Cancer Care Ontario, Toronto, Canada.
Correspondence: Dr SD Walter, Department of Clinical Epidemiology and Biostatistics, McMaster University, HSC-2C16, Hamilton, Ontario, Canada L8N 3Z5. E-mail: walter{at}mcmaster.ca
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Abstract |
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Subjects and Methods A sample survey of naevi in 472 grade 9 secondary school students (aged 1415 years) was conducted in Tasmania, Australia during 1992, and a subset of these individuals was followed up in 1997. Counts of naevi of various sizes were taken on the arm, leg, and back. Naevus density was estimated by using an algorithm to estimate body surface area from the height and weight of an individual. More general relationships of the naevus counts to height and weight were also explored. Finally, we considered whether the relationship between naevus density and the anthropometric variables could be confounded by exposure to ultraviolet radiation.
Results The mean number of naevi was very similar in the two samples. Naevus density was slightly lower in the 1997 sample, mainly because of increasing body size in the cohort. The numbers of naevi were only weakly related to height and weight in males, and there was essentially no relationship in females. Regression analysis showed significant relationships of weight to the back naevus counts in males in 1992 and 1997, and to the arm naevus count in males in 1997; otherwise, none of the regression coefficients for height and weight were statistically significant. This picture did not change following adjustment for potentially confounding variables indicating time spent outdoors or in the sun. Furthermore, there was no evidence that time spent in the sun was related to the body mass index.
Conclusions It appears that the number and density of naevi in an individual are unrelated. Accordingly, with the present state of knowledge concerning the risk of melanoma, both the number and density of naevi should be considered as equally valid in future studies as markers of the risk of melanoma, and in studies on the natural history of naevi. If the disease mechanism is systemic, and not related to particular naevi, naevus density might form the better marker of risk. However, if the disease mechanism is related to effects on particular naevi, then the risk would vary in proportion to the number of naevi.
Keywords Melanoma, naevi, anthropometry
Accepted 7 June 2000
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Introduction |
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It is unclear which of naevus frequency or density might constitute the most appropriate marker of risk for melanoma. If the mechanism of disease induction relates to cellular changes in particular naevi (e.g. as a result of stimulation by exposure to ultraviolet radiation), then the disease risk would vary essentially as the number of naevi. However, the disease mechanism might be more systemic, and not related to specific naevi; in this case, the density of naevi might form a better marker of risk for the individual.
The natural history studies have mainly focused on changes in the number or density of naevi in an individual and they suggest that in Caucasian populations naevus frequency increases rapidly in childhood911,16 and peaks in the teens6,7,14 or early twenties15 and then progressively declines during later life. There are some suggestions that there is a latitude gradient for the age at which the number of naevi peak.12
Little is known about the relationship between naevus frequency and density. It is particularly important to understand this relationship in children, whose body size changes rapidly as they grow. So, for instance, it is not known if the increasing numbers of naevi seen previously in the teen years is really indicative of increasing density or an increase in number consequent on an increasing BSA.
In this paper, we examine the relation between number and density of naevi using data from a recent survey of adolescents in Hobart, Tasmania.13 In particular, we examine the distribution of naevi by body site at two different ages. We evaluate if the number of naevi in an individual is proportional to estimated BSA, and also consider more general relationships of naevus counts to height and weight.
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Methods |
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Naevi were identified using the IARC protocol18 and were counted in two size categories: diameter 2 mm but <5 mm, and diameter
5 mm. Separate counts of palpable lesions were conducted. Protocols for naevus counts have been described elsewhere.13 Naevi were counted by a research nurse on the left arm, right leg and back (including shoulders) in 1992 and on the left arm, back (including shoulders) in 1997. In our analysis, we consider total naevus counts classified by size as 2+ mm, and 5+ mm.
The total BSA (in m2) of an individual can be estimated as
![]() | (1) |
Skin areas for specific body sites are estimated as certain fixed proportions of the total BSA.23 We used 13% as the percentage for the back, 31% for two legs (excluding the feet) and 14% for two arms (excluding the hands). Once the relevant surface areas have been computed, one obtains the naevus density as (naevus count)/(BSA).
Univariate summaries of the various naevus counts were computed. The log transformation of the counts was also investigated, to see if the transformation would eliminate skewness in the distributions, as has been noted previously.12,14 Regressions were computed using the log of the naevus count (N) as the dependent variable, and the logarithms of height (H) and weight (W) as independent variables. Some analyses incorporating adjustments for skin colour and age were done. Skin colour was assessed using the Commission International d'Eclairage L* parameter.13
The basic rationale for the regression model is as follows. If naevus density was constant between individuals, then the naevus count N should be proportional to the individuals' body surface area BSA, i.e.
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![]() | (2) |
Regressions of log(N) on log(H) and log(W) were computed for the 1992 and 1997 data, for each body site. We also computed regressions of N on BSA directly. Further regressions and correlations were computed for the sum of arm, back and leg counts of large (5+ mm) in the 1992 data. To avoid involv-ing the logarithm of zero naevus counts, the transformation log(N + c) was used, with various positive values of c. Sensitivity of the results to the selected value of c was investigated.
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Results |
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For data analysis, all subjects with one or more grandparents born in Asia or Southern Europe were excluded from the data set as the study focus was on determinants of naevi in the higher risk Caucasian population. This left 426 subjects (208 males, 218 females) available for analysis in 1992, and 291 subjects (138 males, 153 females) in 1997. In the 1992 sample, 97% were aged 1415 years.
We compared the distribution of the 1992 baseline variables between the subjects who were followed up in 1997 and those who were not followed up. For most of the variables examined, there was no significant difference between the two groups. This was true, for example, for the time spent in the sun, the lifetime history of sunburns, and the number of naevi counted in 1992. There were, however, some slight differences in height and weight; in both sexes, the individuals who were followed up were slightly taller than the individuals not followed up, and in females the subjects followed up were slightly heavier. Because height and weight were key variables in the analysis, we subsequently carried out separate analyses of the 1992 and 1997 data sets.
Table 1 summarizes the participants' heights and weights, and derived BSA in 1992 and 1997. Limiting attention to subjects observed both in 1992 and 1997, males experienced mean increases of 8.0 cm (5% of 1992 value) in height, 13.4 kg (22%) in weight, and 0.23 m2 (14%) in BSA. The corresponding gains for females were all lower: 2.0 cm (1%) in height, 7.0 kg (12%) in weight and 0.10 m2 (6%) in BSA.
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Table 3 summarizes the naevus density by body site in the two surveys. As was seen for naevus frequencies, naevus density was lower on the back in females compared to males, but arm and leg densities were similar for males and females. There were small percentage differences in naevus density between the two surveys. As seen from the earlier Tables, this is essentially due to increase in body size, with the number of naevi remaining essentially unchanged. The percentage differences in naevus density are slightly larger for females, even though their height, weight and BSA changed less than males.
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Given the generally weak relationships of naevus counts to height and weight, we carried out further regressions to examine the possibility that these relationships might have been confounded by behavioural effects such as the time spent in the sun or time spent outdoors, and an indicator sun behaviour, number of lifetime sunburns. We carried out further regressions, also including an adjustment for skin type (using the L* measure of skin reflectance). None of the basic conclusions were altered, and the coefficients of height and weight in the regressions were also not materially changed by the inclusion of these additional effects.
As a further investigation of the possibility of confounding by ultraviolet exposure, we examined the relationship between body mass index and the time spent in the sun and time spent outdoors. This was to examine the hypothesis that, for example, those who are relatively obese avoid spending time in the sun or outdoors in general. No such relationships were found. There was, therefore, no evidence in these data that the lack of association between naevus frequency and the anthropometric variables was confounded by differences in ultraviolet exposure.
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Discussion |
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Although few investigators have considered the risk associated with anthropometric variables, one recent study24 found significant relationships of melanoma risk to height, weight and BSA. A relationship of height to all causes mortality has also been demonstrated.25 Given that naevi are a risk marker for melanoma, it is, therefore, important to consider their relationship to the physical measurements. In fact, we found in our data that naevus counts are not well predicted by height, weight or estimated BSA. One possible reason for the weak relationship between naevus counts and BSA may be that the square root rule (1) to estimate BSA is in fact not very accurate for all people. Very high accuracy has been claimed for the square root rule,19,26 but it is not clear if such high accuracy would apply in the study population, especially given that the subjects are adolescents. Other reasons for the weak relationship would include measurement error in making the naevus counts, and misattribution of naevi to specific body areas.
With the present state of knowledge, both the number and density of naevi should be considered in principle as equally valid in future studies as markers of the risk of melanoma, and in studies dealing with the natural history of naevi. In fact, as indicated earlier, both number and density of naevi have been used in previous literature, with neither having an obvious advantage. If there are some individuals whose BSA is poorly estimated by rule (1), their naevus density would also be inaccurately estimated. This would argue in favour of the naevus count being chosen as the risk marker, in preference to density. The count is also readily understood by epidemiologists and by the public. On the other hand, the possibility remains that density is the correct risk marker. If so, then density should also be retained as a variable in future analyses.
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