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Web Survey Bibliography

Title A World Wide Web–based survey of nonmedical tattooing in the United States
Year 2012
Access date 31.01.2015
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Abstract

To the Editor: In the United States, recent surveys suggest an increasing prevalence of nonmedical tattooing in younger age cohorts compared with surveys performed only a few years earlier. 1 Given the high use of the Internet by young adults, we sought to estimate the current national prevalence of nonmedical tattoos using a widely disseminated online health assessment system called HowsYourHealth.org 2 open to researchers. This system asks individuals to answer questions about their health status, symptoms, concerns, management of chronic diseases, health care experiences, and self-care. During the period from September to November 2008, we posted two additional questions on the World Wide Web site for respondents aged 14 to 69 years: (1) Have you ever had a tattoo on any part of your body? and (2) How old were you when you had your tattoo? A total of 452 respondents from 43 states responded. Using the survey data, we examined the prevalence of being tattooed by age and gender. We then compared health, social environment, and behavioral risk factors obtained from the survey between those who reported having been tattooed and those who had not been tattooed. We used logistic regression and evaluated the potential confounding effects caused by other factors.

The prevalence of having a tattoo shows strikingly different age patterns. In contrast to the relative stability of adult male tattooing (ie, among men between the ages of 18-49 years a prevalence of 18% and 50-69 years a prevalence of 16%), tattoos in women aged 18 to 49 years (a prevalence of 29%) appeared to be roughly 5 times higher than in women aged 50 to 69 years (a prevalence of 7%) (χ2P < .001). Table I lists the relationships between these women’s health and their social environment and behavioral risks. Of the 13 variables related to having had a tattoo among women 18 to 49 years of age, 3 were statistically significant after adjustment for level of education: sick day, poor relationships, and smoking; these variables would remain below a P value of .05 if corrected for the 13 comparisons using the Bonferroni method.

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Year of publication2012
Bibliographic typeJournal article
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