The head and neck are the body areas exposed to the most solar ultraviolet radiation (UVR), while the face and neck are 2–4 times more sun sensitive than the limbs [
Head and neck melanomas have a poorer prognosis than cutaneous melanomas at other sites [
Accordingly, sun protective hat wearing is an important skin cancer primary prevention strategy which also provides increased protection against ocular UVR damage. A suitable sun protective hat provides complete protection for the scalp and an effective barrier against most direct UVR reaching the face, neck, and ears [
In view of their relatively greater frequency and poorer prognosis, but potentially greater preventability by the physical barrier of a suitably sun protective hat, the head and the neck deserve greater attention for primary prevention. Worldwide, sun exposure is estimated to cause about 65% of cutaneous melanomas, but in regions where high sun exposure occurs, as much as 95% of melanomas and 99% of keratinocyte skin cancers are considered potentially preventable through the avoidance of exposure to harmful UVR levels [
Since early life UVR exposure and sun protection practices contribute to subsequent skin cancer risk, [
Our main study objectives were as follows. While controlling for school demographic factors, to investigate two internationally relevant, potentially relatively easily implemented interventions that are plausible potential statistical predictors of the strength of school sun protective hat policies, namely, (1) membership of a skin cancer primary prevention programme and (2) use of a professional policy drafting service.
We used multivariable modelling of comprehensive cross-sectional New Zealand (NZ) data sourced from the Ministry of Education, [
Under an administratively devolved educational system, each school’s Board of Trustees is responsible for drafting a range of policies, including those relating to sun protection, although the latter is not compulsory. Participation in the SSAP, nationally implemented in 2005 by the Cancer Society of New Zealand, is voluntary and promoted to schools with a student age range of approximately 5–12 years [
Policy documents were sought from the 1,242 schools that participated in the 2017 national survey about sun protection in all schools attended by primary level students [
Interrater reliability (ACLP and AIR) for scoring the outcome variables was initially tested against 20 sequential policies after which adjustments were made to clarify definitions. Reliability for the full study, using the revised criteria and tested between two researchers (BM and AIR) against another 100 randomly selected policies, was 93%. Of the remaining 7% of scores, those clearly in error were then corrected before analysis.
When outdoors during breaks, lunchtimes, excursions, or similar activities, students are required to wear a suitably sun protective hat that provides protection for the face, neck, ears, and eyes [
The second hat-related SSAP criterion specifies that if a hat is not worn then that student is required to play in a shaded area. This was scored dichotomously as either 1 (met the criterion) or 0 (failed to meet the criterion).
Two independent dichotomous variables were investigated as potential statistical predictors of the two policy outcome variables. These variables were as follows: (a) SunSmart status (accredited or not accredited), and (b) whether or not the school had used a professional agency (hereafter designated SchoolDocs) to help draft sun protection policy [
Variables considered controlling for in the multivariable modelling were comparable to those used for an earlier study [
Distribution of school characteristics by response status.
School characteristics | All eligible schools ( | Responding schools ( | Policy ( | Policy accessed ( | ||||
---|---|---|---|---|---|---|---|---|
% | % | % | % | |||||
Integration status | ||||||||
Partnership | 4 | 0.20 | 2 | 0.16 | 0 | 0.00 | 0 | 0.00 |
Private | 69 | 3.43 | 40 | 3.22 | 29 | 2.55 | 14 | 1.66 |
State | 1,678 | 83.48 | 1,039 | 83.66 | 967 | 85.05 | 734 | 87.17 |
State-integrated | 259 | 12.89 | 161 | 12.96 | 141 | 12.40 | 94 | 11.16 |
Socioeconomic decile | ||||||||
1 (lowest)–3 (low) | 559 | 27.81 | 316 | 25.44 | 281 | 24.71 | 206 | 24.47 |
4–7 (medium) | 768 | 38.21 | 479 | 38.57 | 452 | 39.75 | 333 | 39.55 |
8(high)–10 (highest) | 654 | 32.54 | 431 | 34.70 | 394 | 34.65 | 299 | 35.51 |
Missing data | 29 | 1.44 | 16 | 1.29 | 10 | 0.88 | 4 | 0.48 |
Type | ||||||||
Composite (1–10 years) | 2 | 0.10 | 2 | 0.16 | 1 | 0.09 | 0 | 0.00 |
Composite (1–15 years) | 113 | 5.62 | 68 | 5.48 | 51 | 4.49 | 30 | 3.56 |
Restricted composite (7–10 years) | 5 | 0.25 | 3 | 0.24 | 2 | 0.18 | 1 | 0.12 |
Contributing (1–6 years) | 761 | 37.86 | 488 | 39.29 | 459 | 40.37 | 356 | 42.28 |
Full primary (1–8 years) | 1,012 | 50.35 | 615 | 49.52 | 572 | 50.31 | 432 | 51.31 |
Intermediate (7–8 years) | 117 | 5.82 | 66 | 5.31 | 52 | 4.57 | 23 | 2.73 |
Type (dichotomised) | ||||||||
Primary and secondary | 120 | 5.97 | 73 | 5.88 | 54 | 4.75 | 31 | 3.68 |
Primary | 1890 | 94.03 | 1169 | 94.12 | 1083 | 95.25 | 811 | 96.32 |
Overall roll size | ||||||||
Less than 51 | 296 | 14.73 | 166 | 13.37 | 150 | 13.19 | 112 | 13.30 |
51–200 | 706 | 35.12 | 459 | 36.96 | 423 | 37.20 | 328 | 38.95 |
201–400 | 549 | 27.31 | 337 | 27.13 | 309 | 27.18 | 226 | 26.84 |
Greater than 400 | 452 | 22.49 | 275 | 22.14 | 251 | 22.08 | 175 | 20.78 |
Missing data | 7 | 0.35 | 5 | 0.40 | 4 | 0.35 | 1 | 0.12 |
Gender status | ||||||||
Single sex (girls) | 10 | 0.50 | 8 | 0.64 | 4 | 0.35 | 2 | 0.24 |
Single sex (boys) | 9 | 0.45 | 7 | 0.56 | 5 | 0.44 | 2 | 0.24 |
Coeducational | 1,991 | 99.05 | 1,227 | 98.79 | 1,128 | 99.21 | 838 | 99.52 |
Geographic region (N to S)a | ||||||||
Northland/Auckland | 564 | 28.06 | 333 | 26.81 | 291 | 25.59 | 175 | 20.78 |
Waikato/Bay of Plenty | 355 | 17.66 | 213 | 17.15 | 203 | 17.85 | 180 | 21.38 |
Central Districts | 343 | 17.06 | 198 | 15.94 | 179 | 15.74 | 119 | 14.13 |
Wellington/Tasman | 283 | 14.08 | 189 | 15.22 | 170 | 14.95 | 126 | 14.96 |
Canterbury/West Coast | 272 | 13.53 | 185 | 14.90 | 180 | 15.83 | 154 | 18.29 |
Otago/Southland | 193 | 9.60 | 124 | 9.98 | 114 | 10.03 | 88 | 10.45 |
Population density statusb | ||||||||
Rural (<1,000) | 616 | 30.65 | 378 | 30.43 | 351 | 30.87 | 268 | 31.83 |
Minor urban (1,000–9,999) | 216 | 10.75 | 139 | 11.19 | 129 | 11.35 | 107 | 12.71 |
Secondary urban (10,000–30,000) | 112 | 5.57 | 75 | 6.04 | 67 | 5.89 | 60 | 7.13 |
Main urban (>30,000) | 1,061 | 52.79 | 647 | 52.09 | 588 | 51.72 | 406 | 48.22 |
Missing data | 5 | 0.25 | 3 | 0.24 | 2 | 0.18 | 1 | 0.12 |
Accredited | ||||||||
Yes | 826 | 41.09 | 562 | 45.25 | 551 | 48.46 | 527 | 62.59 |
No | 1,184 | 58.91 | 680 | 54.75 | 586 | 51.54 | 315 | 37.41 |
a Cancer Society Divisions. b Ministry of Education categories.
The analyses included most of the variables listed in Table
The chi-squared goodness-of-fit test was used to assess the representativeness of participating schools in terms of school socioeconomic characteristics (Table
Survey responses were received from 1242 (62%) eligible schools, and their distribution according to the characteristics was recorded in the Ministry of Education database, and the policy documentation obtained is presented in Table
Less than half of the schools for which policy documents could be obtained met the optimum score for hat type (Table
Numbers and percentages of schools with hat and shade scores.
Score components (highest = best) | Schools ( | |
---|---|---|
% | ||
Hat score | ||
0 | 113 | 13.42 |
1 | 83 | 9.86 |
2 | 286 | 33.97 |
3 | 360 | 42.76 |
Play in shade score | ||
0 | 149 | 17.70 |
1 | 693 | 82.30 |
The policies of more than 80% of schools met the criterion for specifying shade use when a hat was not worn (Table
With respect to the two dichotomous potential statistical predictors of interest, SSAP status and the use of a professional policy drafting service (SchoolDocs), in Table
Predictors of hat score from multinomial, polytomous logistic regression and meeting of shade requirement from logistic regression.
School characteristic | Hat score highest (3) vs lowest (0) | Hat score 2 vs 0 | Hat score 1 vs 0 | Shade requirement met | ||||
---|---|---|---|---|---|---|---|---|
RRR (95% CI) | RRR (95% CI) | RRR (95% CI) | OR (95% CI) | |||||
Accreditation status | ||||||||
Not accredited | 1 | 1 | 1 | 1 | ||||
Accredited | 4.82 (2.99, 7.79) | <0.001 | 1.88 (1.20, 2.94) | 0.006 | 0.63 (0.35, 1.31) | 0.121 | 3.20 (2.21, 4.64) | <0.001 |
School documents | ||||||||
No policy template | 1 | 1 | 1 | 1 | ||||
Policy template | 8.68 (4.44, 16.96) | <0.001 | 1.28 (0.62, 2.61) | 0.505 | 1.65 (0.72, 3.78) | 0.241 | 3.11 (1.84, 5.26) | <0.001 |
Accreditation status | ||||||||
Not accredited | 1 | 1 | 1 | 1 | ||||
Accredited | 6.48 (3.66, 11.47) | <0.001 | 3.14 (1.82, 5.42) | <0.001 | 1.06 (0.52, 2.17) | 0.865 | 3.28 (2.11, 5.09) | <0.001 |
School documents | ||||||||
No policy template | 1 | 1 | 1 | 1 | ||||
Policy template | 7.47 (3.67, 15.20) | <0.001 | 1.32 (0.62, 2.81) | 0.478 | 1.72 (0.71, 4.21) | 0.231 | 2.70 (1.54, 4.74) | 0.001 |
aModel adjusted for the school socioeconomic variables derived from Table
Inferences between the unadjusted and adjusted models were analogous for both accreditation status and SchoolDocs. Accredited schools were generally associated with an increased relative risk in achieving higher hat scores compared with a lower score (Table
The unadjusted and adjusted logistic regression models also produced similar inferences in the shade analyses. The odds of an accredited school prescribing compulsory shade was 3.28 (CI: 2.11–5.09) times the odds of an unaccredited school. This represents a 228% increase in the odds. Correspondingly, use of SchoolDocs was also associated with an increased odds of incorporating a shade requirement in the school’s sun protection policy (OR: 2.70; CI: 1.54–4.74).
Our study demonstrates that, despite its potential significance for the prevention of head and neck skin cancers, there remains a substantial scope for improvement in NZ primary school sun protection hat wearing policy, with only 43% meeting optimal criteria. This compares to the finding that 62% of school districts in Colorado and California had a sun protection policy for hats with a brim, [
Three of our study findings are relevant for potentially improving this situation. First, we found that SunSmart-accredited schools were significantly more likely than their nonaccredited counterparts to obtain higher and more protective scores for hat wearing and shade use policies. This positive association between membership of an organised school sun protection program and the strength of hat wearing and shade use policies suggests that such programs may help improve the policy by requiring the schools to meet the minimum criteria when applying for accreditation. This is compatible with an Australian finding that SunSmart membership was indirectly related to practice comprehensiveness via policy comprehensiveness [
Second, schools which utilised a professional drafting service for policy development, were more likely to have higher scores than those that did not. This suggests that such services should be encouraged because they may help strengthen policy as well as potentially ensure a more comprehensive, unambiguous specification of all recommended criteria and encourage consistency between schools. There is evidence that a comprehensive written policy is associated with better and more comprehensive sun protection practices [
Third, each of the two key statistical predictors, both SunSmart school accreditation and use of a policy drafting service, produced independent positive associations, because both factors were included concurrently in all models. Although a few isolated, statistically significant relationships between school socioeconomic characteristics and the outcomes of interest were found in the initial modelling, these did not follow any discernibly consistent patterns, were difficult to interpret and, in contrast to the two key predictors, are likely to be less readily targeted or modifiable through the implementation of skin cancer primary prevention interventions. An Australian finding that the relationship between written policy and practice was stronger for remote and regional schools is of interest in this context [
Our study had some limitations. First, although the overall response rate (62%) was acceptable and responding schools did not differ substantially from nonresponders with respect to known socioeconomic factors, those schools for which policies were available for analysis were less representative. Accordingly, it is likely that the study findings reflect a positive response bias, for example, because policies were more likely to be available for accredited than nonaccredited schools. Second, our findings are based on analysis of policy documentation rather than the onsite observation. Actual practice is likely to be less protective than the available data suggest, so onsite studies would be valuable to confirm the differences in practice. Third, since the study was cross-sectional in design, the statistical predictors and outcome variables were not subject to temporal separation, so causation cannot be attributed.
Despite these limitations, our study findings provide support for two relatively straightforward, plausible interventions that could potentially be implemented beneficially in all primary schools via established administrative infrastructure in any jurisdiction, internationally. In both Australia and NZ, such school programmes have been reinforced by broad social marketing mass media campaigns to raise awareness of skin cancer prevention as well as interventions in workplaces and recreational settings. The Australian evidence, in particular, demonstrates that social marketing can be effective not only in motivating behaviour change, reducing sunburn, and increasing awareness but also reducing melanoma rates and having positive economic effects [
The data used to support this study can be made available from the corresponding author upon request.
What is known? (i) The head and neck experience a disproportionate skin cancer burden from solar ultraviolet radiation (UVR) exposure. (ii) Early life sun exposure is linked with subsequent skin cancer risk. (iii) Sun protective hats can provide an effective barrier against solar UVR. What is new? (i) SunSmart schools programme membership and use of a professional policy drafting service are both significantly associated with the most sun protective student hat policies. (ii) These two relatively easily implemented strategies could be applied internationally.
During the drafting of this paper, AIR, BMcN, and A-C LP received salary support via grants to the Social and Behavioural Research Unit from the Cancer Society of New Zealand, which administers the SunSmart Schools programme in NZ. The unit also received support from the University of Otago. Dr. Iosua received salary from the University of Otago. The authors have no financial interest in SchoolDocs Ltd and declare that they have no conflicts of interest.