Melanoma prevalence: can medical literacy overcome the rise in UV radiation? United States as a case study

Abstract

Background: Recent literature shows melanoma prevalence is steadily increasing, mainly due to UV radiation exposure, especially in Caucasians. Skin cancer causes $8.9 billion in direct annual cost and unmeasured indirect costs, but can be prevented by avoiding sun exposure, using protective creams, and regular dermatologists visits for suspicious nevi.

Methods: Using CDC data on non-Hispanic Caucasians, we conducted an Analysis of Variance (ANOVA) to examine the differences in age-adjusted melanoma incidence rates per 100,000. Quadratic Poisson, Ordinary Least Square (OLS) and Two-Stage Least Squares (TSLS) regressions were employed, with UV index and education levels-measured by the percentage of the population holding at least a bachelor's degree-as key explanatory variables.

Conclusion: From a public policy standpoint, raising awareness about sun exposure protection and encouraging regular examinations by professional dermatologists, especially in sparsely populated areas with high UV radiation-could be crucial in reducing the remarkable costs associated with melanoma morbidity and treatment.

Keywords: UV radiation; health literacy; knowledge spillover; melanoma prevalence; population size.

Figure 1

Quadratic Poisson model. This graph is based on column (1) of Table 2, which corresponds to the empirical model A1 including a linear time trend and applied to $n=2,325$ observations. A similar graph based on Column (2) of Table 2, representing the model without a linear time trend, is available upon request.

Figure 2

The ratio of states’ melanoma cases with respect to Alabama (the base category). The graph is based on Column (4) in Table 2. It illustrates how many times the number of melanoma cases (horizontal axis) in each state (vertical axis) surpasses the number in Alabama (the base category) where the population size of the state is controlled.

Figure 3

Ranking of the top 26 states by melanoma prevalence. The graph is based on Column (4) in Table 2. It illustrates how many times the number of melanoma cases (horizontal axis) in each state (vertical axis) surpasses the number in Alabama (the base category) by a factor of more than 1 where the population size is controlled.

Figure 4

The ratio of melanoma cases of each year with respect to the base year (1999). The graph is based on Column (4) in Table 2. It illustrates how many times the number of melanoma cases (the horizontal axis) in each year (the vertical axis) surpasses the number in 1999 (the base category) by a factor of more than 1 where the population size is controlled.

Figure 5

Share of educated population within each U.S. state’s total population. This histogram shows the distribution of the $\mathit{Pop}\_\mathit{BA}$ -to- $\mathit{\text{Population}}$ ratio, where $\mathit{Pop}\_\mathit{BA}$ denotes the number of individuals with a bachelor’s degree or higher, and $\mathit{\text{Population}}$ refers to the total state population.

Figure 6

TSLS estimation of Model B1.

Figure 7

TSLS estimation of Model B2. *Education is proxied as the population holding at least a BA degree minus the minimum value (Pop BA—115,618).

Figure 8

Projected $\mathit{\text{Adjusted Percent}}$ vs. $\mathit{\text{Pred}}\_\mathit{Pop}$ .

Figure 9

Projected $\mathit{\text{Adjusted Percent}}$ vs. $\mathit{UV}2020\mathit{Jm}$ . Figures 8, 9 are based on the estimation results from Model B1, using n = 2,284 observations, as reported in Column (1) of Table 4. Similar graphs based on Column (2) of Table 4 are available upon request.