Proportion of individuals by skin sensitivity exposure within Australia 

03/08/2026

This data visualisation shows the proportion of people aged 15 years and over, by skin sensitivity to sun exposure, across the Australian states and territories between November 2023 and February 2024. The different colours represent individuals' skin reactions after spending 30 minutes in direct sunlight. Orange indicates individuals who burn and do not tan, red represents those who burn first and then tan, pink represents individuals who do not burn and only tan, and purple indicates that no noticeable skin reaction occurs. Overall, this visualisation illustrates how skin sensitivity to sun exposure varies between the different states and territories of Australia. 

'Individuals’ skin type and skin sensitivity to sun exposure can influence sun protection behaviours and associated health risks. The Sun protection behaviours survey asked respondents how sensitive their skin was to burning and tanning. One in four (24.6%) people aged 15 years and over in Australia reported they would ‘just burn and not tan’ after 30 minutes of sun exposure, and one in three (32.9%) people would ‘burn first then tan afterwards’ Over half (57.4%) of Australians reported they would burn after 30 minutes of sun exposure. People living in Tasmania (63.4%), SA (62.6%) and the ACT (61.5%) were more likely to report burning after 30 minutes of sun exposure compared to all Australians (57.4%).' -

Australian Bureau of Statistics. (2024). Sun protection behaviours, Nov 2023 to Feb 2024. In Australian Bureau of Statistics. https://www.abs.gov.au/statistics/health/health-conditions-and-risks/sun-protection-behaviours/nov-2023-feb-2024

My Personal Refelection

I decided to represent this set of data with a drawing of the sun, as it relates to the topic being skin sensitivity from sun exposure. I think my idea was creative, as it took me a while to think of something to picture this data with. I used colour as a pre-attentive feature, as each colour represents a different category which is represented in the key. If I was to redo this data visualization, I would ensure that the category proportions are more accurate. Even though the percentages are written in each quantile, and it's easy to determine the value, the size of each section doesn't always appear to scale, which might throw viewers off.