JMIR FORMATIVE RESEARCH

Foerster et al

Original Paper

Development and Validation of the Epidemiological Tattoo
Assessment Tool to Assess Ink Exposure and Related Factors in
Tattooed Populations for Medical Research: Cross-sectional
Validation Study
Milena Foerster1, Dip Psych, PhD; Lucas Dufour1, DPharm; Wolfgang Bäumler2, Dip Phys, PhD; Ines Schreiver3,
PhD; Marcel Goldberg4, MD, PhD; Marie Zins4, MD, PhD; Khaled Ezzedine5, MD, PhD; Joachim Schüz1, PhD
1

Environment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer, World Health Organisation, Lyon, France

2

Department of Dermatology, University Hospital of Regensburg, Regensburg, Germany

3

Dermatotoxicology Study Centre, Department of Chemical and Product Safety, German Federal Institute for Risk Assessment, Berlin, Germany

4

Population-based Cohorts Unit, INSERM UMS 11, Paris Saclay University, Paris, France

5

University Hospital Henri-Mondor, University Paris Est-Créteil, Créteil, France

Corresponding Author:
Milena Foerster, Dip Psych, PhD
Environment and Lifestyle Epidemiology BranchInternational Agency for Research on Cancer
World Health Organisation
150 cours Albert Thomas
Lyon, 69008
FrancePhone: 33 4 72 73 89 44
Email: foersterm@iarc.who.int

Abstract
Background: Tattooing, whose popularity is growing worldwide, is an invasive body art that involves the injection of chemical
mixtures, the tattoo ink, into the upper layer of the dermis. Although these inks may contain environmental toxins, including
known human carcinogens, their long-term health effects are poorly studied. To conduct the urgently required epidemiologicalstudies on tattoos and their long-term health effects, a validated method for assessing the complex tattoo exposure is needed.
Objective: We aimed to develop and validate the Epidemiological Tattoo Assessment Tool (EpiTAT), a questionnaire toself-assess tattoo ink exposure in tattooed populations suitable for application in large epidemiological cohort studies.
Methods: One of 3 preliminary versions of the EpiTAT using one of the alternative tattoo measurement units hand surface,credit card, or body schemes was randomly filled in by tattooed volunteers in Lyon, France. To identify the most suitable unit oftattoo self-assessment, a validation study was conducted with the selected respondents (N=97) to compare the self-assessmentsof tattoo surface, color, and coverage with validation measurements made by trained study personnel. Intraclass correlation, theKendall rank correlation, and 2-tailed t tests were used to statistically compare tattoo size, color area, and tattoo coverage separately
for each questionnaire version. Participants’ opinions on the alternative measurement units were also considered in the overall
evaluation. For quality control of the validation measures, digital surface analysis of 62 photographs of selected tattoos was
performed using Fiji/ImageJ.
Results: In general, the results revealed overestimation of self-assessed measures compared with validation measures (eg, meantattooed body surface 1768, SD 1547, cm2 vs 930, SD 1047, cm2, respectively, for hand surface; P<.001) and validation measurescompared with digital image analysis (mean individual tattoo surface 147, SD 303.9, cm2 vs 101, SD 154.7, cm2, respectively;
P=.05). Although the measurement unit credit card yielded the most accurate measures for all variables of interest, it had a much
lower completion rate (78/129, 60.5%) than hand surface (89/104, 85.6%) and body schemes (90/106, 84.9%). Hand surface
measured total tattoo size more accurately than body schemes (absolute agreement intraclass correlation coefficient: 0.71 vs 0.64,
respectively).

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

JMIR Form Res 2023 | vol. 7 | e42158 | p. 1
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et al

Conclusions: The final version of the EpiTAT contains 21 items and uses hand surface as a visual unit of measurement. Likert
scales are used to assess color and coverage as a proportion of the total tattoo area. The overestimation of tattoo size by self-reporting
merits further research to identify potential influential factors or predictive patterns that could be considered when calculating
exposure.
(JMIR Form Res 2023;7:e42158) doi: 10.2196/42158
KEYWORDS
tattoos; cancer; questionnaire development; exposure assessment; cohort studies; epidemiology; polycyclic aromatic hydrocarbons;primary aromatic amines; metals; digital surface analysis

Introduction
Background
Despite regulatory efforts, tattoo inks may contain hazardous
substances, including known carcinogens such as metals,
polycyclic aromatic hydrocarbons, and primary aromatic amines[1-5]. These substances, which can induce DNA damage andcell mutations in some exposed organs, can become systemic
after intradermal injection, and this process itself modifies theimmune response [6]. Metals and polycyclic aromatichydrocarbons also accumulate in the draining lymph nodes,
presumably in tattoo pigments deposited there [7-13]. As more
and more people around the world get tattooed, the public healthimpact is rapidly increasing: estimates of tattoo prevalence inindustrialized countries range from 15% to 20% for all adultage groups combined and exceed 40% in age groups <40 years
in the United States [14].
Surprisingly, no large-scale epidemiological studies haveexamined the potential carcinogenicity of tattoo inks until now.
To our knowledge, only 2 small case-control studies, bothpublished in 2020, have investigated the cancer risk associatedwith tattooing [15,16]. Warner et al [15] found no association
between tattoos and non-Hodgkin lymphoma or multiple
myeloma using data from 2 case-control studies that collected
data between 2000 and 2004 (non-Hodgkin lymphoma) andbetween 2009 and 2013 (multiple myeloma) in British
Columbia, Canada. Barton et al [16] examined the association
between tattoos and basal cell carcinoma in a case-control study
from New Hampshire, United States, that collected data in 2
phases between July 2001 and June 2002 and between July 2012
and June 2014. The authors found a possible increased risk ofearly basal cell carcinoma at the site of cosmetic tattoos
compared to a non-tattooed body-part. Of note, both studies arelimited by significant methodological shortcomings. Not only
are sample sizes small with only a few exposed individuals
leading to low power, particularly with regard to exposure
assessment, which is a crucial part of epidemiological research,
but the studies also show deficits. Although Warner et al [15]did not have information on tattoo color, location, or bodysurface covered, Barton et al [16] lacked information on tattoo
surface and age. All these factors have an impact on systemic
exposure, which is determined by the amount and type of
pigment in the body.

Objectives
A scientifically based exposure assessment is a crucial part ofepidemiological studies to establish the potential relationshiphttps://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

between exposure and adverse human health outcomes, reducebias, and allow estimation of dose-response relationships [17].
Estimating tattoo exposure requires knowledge of visual factors
such as tattoo size, color, and coverage, as well as contextual
factors such as the age of the tattoo, expertise of the tattoo artist,or potential modifying factors such as exposure to the sun of
the tattooed body part. Ideally, tattooed body surfaces would
be assessed by physical visual examination, 3D body modeling,
or image analysis. However, for large epidemiological research
populations, these methods are not practical because of
economic or ethical constraints. Exposure assessment byquestionnaire can be a cost-effective and rapid alternative but
requires validation to ensure accurate measurement of key tattoo
characteristics to avoid response bias [18]. The aim of this study
was therefore to develop and validate a questionnaire to assess
detailed information on tattoo exposure in large populationgroups and at the same time identify potential uncertainties andbiases that can be taken into account in subsequent exposure
calculations.
The Epidemiological Tattoo Assessment Tool (EpiTAT), whose
validation is presented here, will be used for exposure
assessment in the French and German national cohorts Cohortedes consultants des Centres d’examens de santé (Constances)and Nationale Kohorte (NAKO) [19,20].

Methods
Questionnaire Development
The EpiTAT was developed in collaboration with an expert
panel consisting of members of the European Society of Tattoo
and Pigment Research and the authors’ epidemiological research
department to ensure that the knowledge of tattoo experts andtechnical excellence in epidemiological exposure assessment
was represented. In addition, tattoo artists were consulted during
the development. Relevant factors of tattoo exposure wereidentified to structure the questionnaire into four topics dealing
with (1) appearance of tattoos (size, location, and colors), (2)contextual characteristics (age of the tattoo, country of tattooing,
expertise of tattooists, and overlay or cover-up [ie, tattoos
covering previously tattooed skin]), (3) known complicationsof tattoos (allergic reactions, infections, itching, andgranulomas), and (4) UV light exposure (sun exposure and sun
protection) and laser exposure (tattoo removal).
To identify an appropriate unit of measurement for the visualcharacteristics of tattoo exposure (size, color, and coverage ofthe tattoo), 3 different versions of the questionnaire weredeveloped to measure tattoo exposure in the 3 alternative test
JMIR Form Res 2023 | vol. 7 | e42158 | p. 2
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
units hand surface, credit card, and body schemes. Although
in the hand surface and credit card questionnaires, the visualcharacteristics were measured directly by the respective unit ofmeasurement per body part, in the body schemes questionnaire,
the participants were asked to represent their exposure according
to the most appropriate of 5 different exposure scenarios per
body part concerning 10%, 25%, 50%, 75%, and 100% of thetattooed body surface (Multimedia Appendix 1). As visual aids,
a color chart to assess tattoo color and graphic diagrams related
to the different degrees of tattoo coverage (10%, 25%, 50%,
75%, or 100%; relating to the inked parts within the total surface
area of the tattoo, including blank spaces) were used in all 3
questionnaires (refer to item 3 and 4, respectively, of the finalquestionnaire presented in Multimedia Appendix 2). Although
in the hand surface and credit card questionnaires, the coloredand filled areas were directly sampled in the unit ofmeasurement, 5-point Likert scales were used for each colorand degree of coverage to estimate the respective tattooed area
per body part in the body schemes questionnaire. All otherquestionnaire items were the same for all 3 questionnaires. The
wording of the questions followed strict wording rules for thedevelopment of the questionnaires to avoid ambiguities andnegative questions, reduce technical jargon, and improve
simplicity [18]. The questions generally covered all tattoos
combined (instead of asking them one by one). The preferred
response options for the questionnaire were multiple choice andLikert scales. The resulting questionnaires were reviewed by
the expert panel and presented at the World Congress of Tattoo
and Pigment Research 2021 in Amsterdam, the Netherlands,
for an open round of expert comment.
Digital versions of the 3 questionnaires were programmed using
the REDCap (Research Electronic Data Capture; Vanderbilt
University) web-based data collection tool. A final question
was added to ask participants whether they were interested in
the validation study and, if so, to leave their contact details forfurther contact.

Data Collection
To compare self-reported and validated tattoo exposure for eachof the 3 questionnaire versions, data were collectedcross-sectionally by (1) study participants completing 1 of the
3 versions of the digital questionnaire (self-assessed data) and(2) study staff trained in accurate validation measurements witheach participant separately (validation data).
To collect the self-reported data, the study was advertised onsocial media and via printed flyers at tattoo studios, gyms, cafes,
and university billboards in the city of Lyon, France. The
advertisements displayed QR code links to the 3 digital versionsof the questionnaire. To collect the validation measure, we
invited participants from the pool of web-based respondents,
equally distributed across the 3 versions of the questionnaire,
to a face-to-face meeting, respecting the COVID-19–related
restrictions. Because of the unexpectedly high proportion ofinvited respondents with few or no tattoos, the selection ofparticipants was adjusted post hoc in favor of respondents withlarge and colored tattoos to obtain a more heterogeneous
distribution of exposure. The validation study consisted of aninterview and a visual inspection of the participants’ tattoos,
https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

Foerster et al
guided by a questionnaire. For the validation, a dedicatedvalidation questionnaire was programmed on a tablet device
via the KoBo Toolbox web-based data collection tool. The
questionnaire consisted of a repeatable sequence of questions
asked for each tattoo. This sequence included visualcharacteristics (location, size, coverage, and color) andcontextual characteristics (eg, age of tattoo and expertise of
tattooist), as well as the collection of image data via an
integrated photograph function. In practice, participants wereasked to show their tattoos one after the other to be measured
by trained study staff (the study coordinator and an assistant).
The length and width of each tattoo were assessed using a tapemeasure, and its area was calculated using the optically closest
geometric shape, including squares (length²), rectangles(length×width), circles (radius²×π), ovals (radius1×radius2×π),
and their possible combinations. These judgments always related
to the total surface of the tattoo; for example, in the case of bold
letters, the geometrical shape of a whole word was consideredinstead of each letter separately. Next, the coverage of the tattoo
was judged via the graphic aid used in the test questionnaires.
With the help of the color chart of the tattoo questionnaire, therespective area was visually estimated as a proportion of thetattoo area and translated into square centimeters. With
additional written consent, up to 2 photographs of each tattoo
were taken, depending on the size and location of the tattoo. A
measuring tape was included in each photograph for later
calibration. The hand surface questionnaire included
measurements of the length and width of the hand, which werealso measured by study staff for validation purposes. As a finalquestion, participants were asked to give oral feedback on theversion of the questionnaire they had originally completed. Theinterviews lasted between 15 and 60 minutes, depending on thenumber and colors of the tattoos. Participants were paid €50(approximately US $56) each, plus travel expenses for public
transport in Lyon, if necessary.

Statistical Analysis
For self-assessed exposure, tattoo size measured via handsurface and credit card was translated into square centimeters,
overall and by tattoo color and tattooed body part, by
multiplying the numerical value by the measured surface areaof the hand or standard credit card (30 cm2). For the size of thetattoos measured by body schemes, the total sex-stratified bodysurface area of each participant was first calculated using the
Schlich formulas 0.000975482×weight0.46×height1.08 for womenand 0.000579479×weight0.38×height1.24 for men [21]. Next, thebody surface area in square centimeters per body part wascalculated by multiplying the total body surface area by acorresponding body part derived by the modified rule of nines,
a standardized body partitioning used for skin burns [22].
Finally, the derived limb areas were multiplied by thecorresponding tattooed area, overall and by color, to calculate
the tattooed area in square centimeters.
To estimate the total tattoo coverage, for hand surface and credit
card, the units of tattooed areas were multiplied by the indicatedcoverage proportion (0.1, 0.25, 0.5, 0.75, and 1) and then divided
by the total tattooed area. For body schemes, the individual areasof the tattooed limbs were multiplied by the indicated coverage
JMIR Form Res 2023 | vol. 7 | e42158 | p. 3
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
proportion, added together, and their sum divided by the total
tattooed body area.
For the validation questionnaire, the tattoo size was calculated
by summing the measured tattoo areas, overall and by color per
body part. The overall tattoo coverage was calculated by
dividing the sum of the products of the individual tattoo size
and the respective coverage proportion by the total tattooed
body area and transformed into percentage.
Summary statistics for tattoo size, color, and tattoo coveragefor the 3 versions of the questionnaire were calculated, and themeans were compared using 2-tailed t tests for dependent
samples. For tattoo size, color, and coverage percentages, thefollowing validation methods were used to compare them with
self-reported measures. Absolute agreement intraclasscorrelation coefficients (AA-ICCs) and consistency of agreement
intraclass correlation coefficients (CA-ICCs) were used tocompare absolute interrater reliability and consistency. Raw
values and assigned ranks were compared visually using
scatterplots, and rank correlation was estimated using Kendall
τ. Bland-Altman plots were calculated to visualize the difference
in response interval between self-rated and validation measuresin
relation
to
their
mean
tattoosize
22([cm validation–cm self-assessment]/2).
To assess the quality of the validation measurements, the blackand colored surfaces of the selected tattoo photographs wereanalyzed using the open-source image analysis software
Fiji/ImageJ (version 2.3.0/1.53q). The photographs were
calibrated using a known distance in centimeters taken fromthe measuring tape included in each photograph. The black andgray images were then transformed to 8-bit images, and amanual or automatic threshold was set according to the tattooed
body area. The tattooed area in the resulting binary image wasmeasured using a freehand selection tool and the analyze
particles command. The colored images were analyzed using
the Trainable Weka Segmentation plugin, which separates thecolor shades into classes using user-guided machine learning.
The resulting black-and-white probability maps for each color
shade were analyzed in the same way as the black or graytattoos. To validate the measurements, for each binary image,3 different thresholds were set, and the average of themeasurements was taken.
The raw surface measurements and assigned ranks obtained via
Fiji/ImageJ were compared visually with the physical validation
measurements (tattoo surface×coverage), globally and bycolored and black or gray surfaces via scatterplots. Interrater
reliability and Kendall τ were calculated via the intraclasscorrelation coefficient (ICC).

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

Foerster et al

Ethical Considerations
Human participant research ethics approval for this study was
obtained from the French Comité de Protection des Personnes(CPP 2021/48) and the International Agency for Research on
Cancer Ethics Committee (IEC 21-17). All participants received
a study information sheet that contained information about thebackground of the study (potential long-term health effects of
tattoos, particularly in terms of cancer, and the necessity of
exposure assessment) and a detailed description of the physicalvalidation measurements, as well as a section informing
participants that they had the right to withdraw from the study
at any time without giving any justification. After providing
participants the opportunity to ask any questions regarding thestudy, we asked them to provide written consent to participate
in the study, and if they agreed, they were asked to consider
providing consent to have photographs taken of each tattoo.
Each study participant was previously deidentified via analphanumeric code generated in the web-based questionnaire.
The study coordinator did not have access to identifiable dataof the participant. All study participants received €50(approximately US $56) as compensation for their timely effort
to participate in the study.

Results
Questionnaire Completion
Of the 339 people who initiated 1 of the 3 versions of thequestionnaire between November 16, 2021, and March 29, 2022,
a total of 257 (75.8%) finally completed the questionnaire(Figure 1). Completion rates were higher for the hand surface
version (89/104, 85.6%) and the body schemes version (90/106,
84.9%) than for the credit card version (78/129, 60.5%).
Of the 257 people who completed the questionnaire, 99 (38.5%)
were invited to a validation interview (33/89, 37%, from thehand surface version; 33/90, 37%, from the body schemes
version; and 33/78, 42%, from the credit card version). Of these99 people, 1 (1%) was excluded because of a technical error,and 1 (1%) was excluded because of apparently random
responses to the questionnaire, leaving 97 (98%) participantsin the final sample. Two-thirds (66/97, 67%) of the participants
were women, and the mean age of the participants was 27.2
(SD 6.2) years (Table S1 in Multimedia Appendix 3). The
median number of tattoos was 5 (IQR 2-9), and 23% (22/97)of the participants had a single-color black tattoo, 25% (24/97)
a gray tattoo, and 52% (51/97) a colored tattoo (defined as thepresence of at least one color other than black or gray, including
white; Table 1).

JMIR Form Res 2023 | vol. 7 | e42158 | p. 4
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et al

Figure 1. Flowchart of derivation of the study sample via web-based data collection of self-assessed exposure data.

Table 1. Study population profile, overall and by questionnaire version.
All (N=97), n (%)

Hand surface (n=32), n (%) Credit card (n=33), n (%) Body schemes (n=32), n (%)

Black

22 (23)5 (16)

6 (18)

11 (34)

Gray wash

24 (25)8 (25)

9 (27)

7 (22)

Colored51 (52)19 (59)18 (55)

14 (44)

Color

Tattoo age, years (multiple answers allowed)<1

55 (57)17 (53)19 (58)18 (56)

1 to <5

79 (81)26 (81)28 (85)25 (78)5 to <10

33 (34)10 (31)

10 (30)13 (41)10 to <15

9 (9)4 (13)

2 (6)

3 (9)

≥15

6 (6)

4 (13)

2 (6)

0 (0)

Tattoo artist’s expertise (multiple answers allowed)
Experienced artist, tattoo studio95 (98)31 (97)33 (100)

31 (97)

Experienced artist, elsewhere

29 (30)9 (28)

10 (30)10 (31)

Nonexperienced person, at home

19 (20)5 (16)

8 (24)

6 (19)

Other circumstances

3 (3)

1 (3)

0 (0)

2 (6)

At least one tattoo acquired outside
France36 (37)9 (28)

12 (36)15 (47)

Any tattoo complication (self-assessed)

16 (16)5 (16)

4 (12)

7 (22)

Tattoo Size
The mean self-rated tattoo size was overestimated comparedwith the validated tattoo sizes in hand surface (1768, SD 1547,
cm2 vs 930, SD 1047, cm2, respectively; P<.001) and bodyschemes (2301, SD 2197, cm2 vs 923, SD 1334, cm2,
respectively; P<.001) but not in the credit card questionnaire(734, SD 1222, cm2 vs 677, SD 1112, cm2, respectively; P=.56;
Table 2; Figure 2; Figure S1 in Multimedia Appendix 3).
Although the highest relative overestimation was observed forsmall tattoos, the absolute overestimation in square centimeters
https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

was highest for large tattoos (Figure 3). Absolute agreement
between the self-report and validation measures for tattoo size
was high for credit card (AA-ICC=0.89) and moderate for handsurface (AA-ICC=0.71) and body schemes (AA-ICC=0.64). In
terms of consistency, all 3 measures were highly reliable(CA-ICC for hand surface=0.85, CA-ICC for credit card=0.89,
and CA-ICC for body schemes=0.82).
The rank correlation between the self-report and validation
measures was generally very high, with Kendall τ=0.82 for thecredit card questionnaire, followed by Kendall τ=0.72 for handsurface and Kendall τ=0.69 for body schemes (Figure 4).
JMIR Form Res 2023 | vol. 7 | e42158 | p. 5
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et al

Table 2. Descriptive and quality measures of 3 different measurement units to measure tattoo surface and coverage.
Values, mean (SD)

Values, median (IQR)

P valuea

AA-ICCb

CA-ICCc

Kendall τ

<.001

0.71

0.85

0.72

.56

0.89

0.89

0.82

<.001

0.64

0.82

0.69

.18

0.34

0.35

0.26

.05

0.70

0.72

0.59

.47

0.67

0.67

0.52

Tattoo size (cm2)
Hand surface (n=32)
Self-assessment

1768 (1574)

1324 (467-2589)

Validation

930 (1047)

403 (124-1550)

Credit card (n=33)
Self-assessment

734 (1222)

277 (185-716)

Validation

677 (1112)

217 (93-487)

Body schemes (n=32)
Self-assessment

2301 (2197)

1531 (708-2450)

Validation

923 (1334)

310 (192-1123)

Coverage (%)
Hand surface (n=32)
Self-assessment

52 (23)51 (39-66)

Validation

46 (20)46 (25-63)

Credit card (n=33)
Self-assessment

50 (28)52 (26-69)

Validation

44 (21)45 (29-61)

Body schemes (n=32)

aSelf-assessment

52 (21)52 (41-68)

Validation

50 (21)50 (34-67)

P values calculated via 2-tailed t tests for dependent samples.

b

AA-ICC: absolute agreement intraclass correlation coefficient.

c

CA-ICC: consistency of agreement intraclass correlation coefficient.

Figure 2. Total tattooed body surface (measured in square centimeters) measured by 3 different test measurement units plotted against the corresponding
size measured in the validation study in 97 tattooed participants. Because of the left-skewed distribution of tattoo size, values are plotted on logscale.

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

JMIR Form Res 2023 | vol. 7 | e42158 | p. 6
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et al

Figure 3. Bland-Altman plot (difference plot) of tattoo surface measured via self-assessment versus validation data for 3 different measurement units
using data from the whole study population (N=97).

Figure 4. Scatterplot of assigned ranks of self-assessment versus validation data of total tattoo surface for 3 different measurement units using datafrom the whole study population (N=97).

Tattoo Color
For 29% (28/97) of the participants, gray (including diluted
black, called gray wash) was detected by the validation measuresin at least one tattoo that was not reported in the self-report. By
contrast, for 6% (6/97) of the participants, any other color was
detected by the validation measures in at least one tattoo thatwas not reported in the self-report. Similarly, 6% (6/97) of theparticipants reported gray or any other color in the test
questionnaires that was not seen in the validation measures.
Because of the high number of misinterpretations of gray as
black, we combined the 2 for further analysis. Also, all nongray
or nonblack color surfaces were added together to form a genericcolor surface because of the small sample size of individualcolors.
For those with colored tattoos, the average black or gray area
was overestimated in the self-assessed measures compared withthe validation measures via hand surface (2178, SD 2078, cm2
vs 986, SD 968, cm2, respectively; P=.005) and via bodyhttps://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

schemes (2986, SD 3027, cm2 vs 1382, SD 1731, cm2,
respectively; P=.004; Table 3; Figures S2 and S3 in Multimedia
Appendix 3). For credit card, the self-assessed and validation
measures for the average black or gray area were comparable,
but the average area of the colored tattoo was considerably
smaller than that of the colored tattoo for hand surface and bodyschemes (self-assessed measure: 528, SD 519, cm2; validation
measure: 460, SD 532, cm2; P=.28; Table 3). The total coloredarea differed significantly between the self-assessed andvalidation measures only for the measure hand surface (824,SD 899, cm2 vs 320, SD 321, cm2, respectively; P=.02; Figures
S4 and S5 in Multimedia Appendix 3). The self-assessed andvalidation measures for credit card (196, SD 246, cm2 vs 200,
SD 297, cm2, respectively; P=.87) and body schemes (235, SD
285, cm2 vs 103, SD 108, cm2, respectively; P=.12) did not
differ significantly.
For participants with colored tattoos, absolute interrater
reliability and consistency were very good for the credit card
JMIR Form Res 2023 | vol. 7 | e42158 | p. 7
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et alversion for the estimation of colored and black or gray areas(colored: AA-ICC=0.95, CA-ICC=0.94; black or gray:
AA-ICC=0.87, CA-ICC: 0.87; Table 3). For the hand surface
version, interrater reliability was low for colored surfaces andlow to moderate for black or gray surfaces (colored:
AA-ICC=0.28, CA-ICC=0.35; black or gray: AA-ICC=0.44,
CA-ICC=0.55), whereas for body schemes, interrater reliability
was moderate to high for black or gray surfaces (AA-ICC=0.69,
CA-ICC=0.82) but low for colored surfaces (AA-ICC=0.29,
CA-ICC=0.33).

The agreement among the ranks comparing self-assessed andvalidation measures was strong for all 3 versions of thequestionnaire for colored and black or gray surfaces.
Correlations were again strongest for the credit card version(colored: Kendall τ=0.66; black or gray: Kendall τ=0.78),
followed by the hand surface version for colored surfaces(colored: Kendall τ=0.65; black or gray: Kendall τ=0.7) andbody schemes for black or gray surfaces (colored: Kendall
τ=0.42; black or gray: Kendall τ=0.78; Figures S6 and S7 in
Multimedia Appendix 3).

Table 3. Descriptive and quality measures of 3 different measurement units to measure tattoo colors.
Values, mean (SD)

Values, median (IQR)

P valuea

AA-ICCb CA-ICCc

Kendall τ

.005

0.44

0.55

0.7

.28

0.87

0.87

0.78

.004

0.69

0.82

0.78

.02

0.28

0.35

0.65

.87

0.95

0.94

0.66

.12

0.29

0.33

0.42

Black or gray surface (cm2)
Hand surface (n=19)
Self-assessment

2178 (2078)

1796 (525-3053)

Validation

986 (968)

594 (183-1632)

Credit card (n=18)
Self-assessment

528 (519)

277 (139-693)

Validation

460 (532)

250 (72-858)

Body schemes (n=14)
Self-assessment

2986 (3027)

1663 (920-4123)

Validation

1382 (1731)

516 (135-2245)

2

Colored surface (cm )Hand surface (n=17)
Self-assessment

824 (899)

565 (170-1181)

Validation

320 (321)

221 (53-472)

Credit card (n=16)
Self-assessment

196 (246)

72 (49-324)

Validation

200 (297)

50 (21-257)

Body schemes (n=12)

a

Self-assessment

235 (285)

91 (36-402)

Validation

103 (108)

68 (12-191)

P values calculated via 2-tailed t tests for dependent samples.

b

AA-ICC: absolute agreement intraclass correlation coefficient.

c

CA-ICC: consistency of agreement intraclass correlation coefficient.

Tattoo Coverage
The mean percentage of self-reported tattoo coverage comparedwith the validation measure differed but not significantly forthe 3 questionnaires (hand surface: 52%, SD 23%, vs 46%, SD
20%, respectively; P=.18; credit card: 50%, SD 28%, vs 44%,
SD 21%, respectively; P=.05; body schemes: 52%, SD 21%, vs50%, SD 21%, respectively; P=.47; Table 2; Figure S8 in
Multimedia Appendix 3). The concordance of the measures was
low for hand surface (AA-ICC=0.34, CA-ICC=0.35) andmoderate for credit card (AA-ICC=0.70, CA-ICC=0.72) andbody schemes (AA-ICC=0.67, CA-ICC=0.67). Tattoo coverage

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

was generally slightly overestimated, especially with the handsurface unit (Figure S9 in Multimedia Appendix 3).
Rank correlations between self-reported and validation measures
were strong for credit card (Kendall τ=0.59) and body schemes(Kendall τ=0.52) but considerably weaker for hand surface(Kendall τ=0.26; Figure S10 in Multimedia Appendix 3).

Reliability of the Validation Measures
The surface area of 62 photographs of tattoos, of which 24(39%) were colored, was analyzed using Fiji/ImageJ. The mean
and median areas of these tattoos were 147 (SD 303.9) cm2 and49 (IQR 9-130) cm2, respectively, in the validation study
JMIR Form Res 2023 | vol. 7 | e42158 | p. 8
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
compared with 101 (SD 154.7) cm2 (P=.05) and 42 (IQR 9-97)
cm2, respectively, in the digital surface analysis (Figure 5; raw
values not shown). The ICC indicated high absolute agreementof the 2 measures (AA-ICC=0.73) as well as high consistency(CA-ICC=0.85). The rank correlation of the 2 measures wasvery high (Kendall τ=0.84). In the colored tattoo subset, themean and median black or gray areas were 115 (SD 220.6) cm2
and 38 (IQR 22-136) cm2, respectively, in the validation study
compared with 85 (SD 106.4) cm2 and 46 (IQR 24-110) cm2,

Foerster et al
respectively, in the digital surface analysis (Figure S11 in
Multimedia Appendix 3). For the colored areas, the means andmedians were 58 (SD 70.3) cm2 and 40 (IQR 30-52) cm2,
respectively, in the validation study compared with 35 (SD 32.1)
cm2 and 22 (IQR 15-49) cm2, respectively, in the digital area
analysis. Reliability measures were lower than for total surface
area but still quite high (black or gray: AA-ICC=0.74,
CA-ICC=0.85; Kendall τ=0.67; colored: AA-ICC=0.63,
CA-ICC=0.77; Kendall τ=0.67; Figures S12 and S13 inMultimedia Appendix 3).

Figure 5. Scatterplot of 62 individual tattoo surfaces measured in the validation study versus digital image analysis of tattoo photographs via thesoftware Fiji/ImageJ. Because of the left-skewed distribution of tattoo size, values are plotted on logscale.

Discussion
Summary of Principal Findings
In this project, we developed and validated, by comparing 3
alternative measurement units, the EpiTAT, which, to ourknowledge, is the first questionnaire to measure tattoo exposurein epidemiological research and for other scientific purposes.
The EpiTAT, which will be first used in the French (Constances)and German (NAKO) national cohorts, includes 21 items. It
assesses visual (tattoo size, colors, shading, and coverage) andcontextual (age of the tattoo, artist’s expertise, and country oftattooing) characteristics of tattoos, as well as potential
mediators of ink exposure (UV light and laser exposure) andshort-term tattoo complications (Multimedia Appendix 2), allfactors needed for epidemiological risk assessment of tattoos.
Through quantitative and qualitative comparisons, we identified
the measurement unit hand surface as more suitable forself-assessment of total tattoo surface than the alternative units
credit card and body schemes. Because of weak correlations
between self-assessment and validation measures for the visualtattoo features color or colors and coverage when measured
with numeric measurement units, Likert scales seem preferable
for judging these features. Finally, we also identified apronounced overestimation of self-assessed tattoo surface
compared with validation measures.

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

Detailed Discussion
Choice of Measurement Unit
At first sight, our results indicate a better accuracy and interrater
reliability for the credit card version of the questionnaire.
However, the completion rate for this version (78/129, 60.5%)
was approximately 25% lower than the completion rates for thehand surface (89/104, 85.6%) and body schemes (90/106,
84.9%) questionnaires. This low completion rate probably
induced a participation bias in the data because more attention
and patience are required to complete this questionnaire owing
to the small size of the measurement unit, which was confirmedby the personal comments of the study participants. Of the 33
participants in the credit card group, 8 (24%) mentioned thatthe credit card measurement was cumbersome, but only 16%(5/32) did so for hand surface (of these 5 people, 2, 40%, hadtattoos on their backs), and only 3% (1/32) did so for bodyschemes. More importantly, the average tattooed body area wasby far the smallest in the credit card group, suggesting thatpeople with larger tattoos abandoned this questionnaire more
often. Although the interrater reliability values of the handsurface and body schemes versions were comparable, the bodysurface area derived in square centimeters via body schemes
lacked precision because of its dependence on multiple estimatedparameters (ie, body limb areas extrapolated by distribution of
total body surface area, which is itself based on estimates). As
this procedure was used to calculate tattoo areas for the
self-report and validation measures, a possible misestimation
would not be reflected in the ICC. By contrast, the hand surface
questionnaire enhanced precision by asking participants to
JMIR Form Res 2023 | vol. 7 | e42158 | p. 9
(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
measure the length and width of their hands with a ruler if
possible (which three-fourths—25/32, 78%—of the participantsdid) or to estimate the length and width using a standard (17.5cm × 9.5 cm) surgical mask as a reference that helped totranslate the hand unit into square centimeters. In the printed
version of the questionnaire used for data collection in the
NAKO and Constances cohorts, a printed ruler is included.
Finally, hand surface area has a direct relationship with bodysurface area in normal-weight individuals, which allows a directcomparison of tattooed body proportions via raw values [23].
For all these reasons, the hand surface was chosen as the mostappropriate unit of measurement, given its superiority in termsof accuracy compared with body schemes and the fact that it
may avoid the possible participation bias observed for the credit
card version.

Assessment of Tattoo Colors
Knowledge of the colored area of a tattoo is essential for
exposure assessment because particular colors are associatedwith specific classes of chemicals, which is reflected in ourgrouping of color categories. However, measuring the coloredsurfaces of tattoos is anything but straightforward. Color fading,artistic effects such as color gradients or color dispersion,
subjective color perception, and multiple distant placements ofthe same colors make it almost impossible to visually assess
the area of a single color, especially if many different colors
are used in a single tattoo. We observed low correlations
between the self-report and validation measures for colored
areas estimated via the unit hand surface or via a 5-point Likert
scale in the body schemes questionnaire, an indication of the
difficulties involved in accurately measuring the colored surfacesof tattoos. Again, credit card measured the colored areas much
more accurately, but, as with total tattoo size, a systematic bias
cannot be excluded. In the other 2 questionnaires, the colored
areas were generally overestimated, with the overestimation
factor being higher for hand surface. Feedback from participantssuggested that measuring color by hand surface was difficult,whereas measurement by Likert scale (body schemes
questionnaire) was very well received, although concerns wereexpressed about the accuracy of the measurement. The true
proportion of color was often suspected to be between
categories. Because of these findings and ideas, we finallysettled on a 10-point ordinal Likert scale to measure individualcolor proportions for all tattoos combined. Another difficulty
observed was the differentiation of black from gray wash.
Depending on the personal style of tattoo artists, the opticalimpression of shading is technically produced through diluting
black ink with distilled water or another liquid to achieve graywash, mixing black and white ink, drawing technique (eg,dotwork), or their combinations. In our study, many participants
seemed to be unaware of these differences, and shading wasoften generically classified as black. Because of this veryfrequent error, a common color category for black or gray or
shading was chosen for the final questionnaire to avoid
confusion. The nuances of exposure to black ink are further
covered by the judgment of tattoo coverage, a question we
refined in the final questionnaire, as discussed in the next
paragraph.

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

Foerster et al

Tattoo Coverage
The coverage of a tattoo, often related to the style of the tattoo,
is a major determinant of the ink exposure of the tattoo andshould therefore be evaluated. We used graphical diagrams torepresent the different proportions of tattoo coverage. Although
this self-invented method was well received, coverage wassometimes overestimated. In particular, participants with graphic
ethnic tribal or bold text tattoos were unsure about the choiceof category, that is, whether a tattoo was completely coveredin with respect to large covered areas or only partially coveredin with respect to untattooed spaces between single letters,
elements, or shapes. In the final version of the questionnaire
we took this misunderstanding into account by adding an
explanatory note to the relevant question. Regarding the 3
different versions of the questionnaire, the coverage wasestimated more adequately by the credit card and body schemes
versions than by the hand surface version. As explained in the
Choice of Measurement Unit section, a participation bias could
have influenced the results of the credit card version toward amore accurate measure. For this reason, we decided to use a
Likert scale as applied in the body schemes questionnaire forthe final version of the EpiTAT. In line with the color measure,the initial Likert scale was increased from 5 to 10 points to givethe participants the possibility of making a more nuanced
judgment.

Identification of Bias
On average, participants measuring their tattoos with theultimately chosen unit of measurement hand surface
overestimated their tattoo area by approximately 2 times, andalthough the overestimation factor was particularly high forsmall tattoos (4-fold for the smallest 25% of the validated tattoo
areas), the absolute overestimation was >3 times higher forlarger tattoo areas (largest 25% of the validated tattoo areas)than for smaller tattoo areas. In case of dose-dependent healtheffects of tattoo inks, this overestimation has to be taken into
account for a proper interpretation in the risk assessment. The
actual tattoo area and thus exposure is likely to be lower than
the tattoo area assessed by this and other questionnaires. If, in
future research, such dose-dependent relationships are found,post hoc calibrations might be applied, especially in individuals
classified as highly exposed. On a positive note, the risk ofrecall bias, a common problem in epidemiological studies using
self-reported exposure assessment, is minimized owing to thepermanent visibility of tattoos [18].

Limitations
This validation study includes some limitations. First, althougha measuring tape was used in the validation study, and themeasurements were cross-validated by 2 examiners, subjectivity
remains an issue. However, we performed a digital image
analysis of a selected subset of tattoo photographs, all of which
met the minimum requirements for digital image analysis: a90-degree angle and well-balanced brightness and contrast.
Although we identified a slight overestimation of tattoo surfaces,
particularly if they were colored, in the measurement tapevalidation compared with the Fiji/ImageJ analysis, the overall
agreement between the 2 was very high. For future research,
we recommend using digital surface measures of tattoo
JMIR Form Res 2023 | vol. 7 | e42158 | p. 10(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
photographs instead of subjective validation via measurementtape to judge the reliability of self-assessed measurements. As
we found Fiji/ImageJ to be a suitable software tool for surface
analysis, we added a visual element to the final questionnaire:participants are now asked to mark the location and size of theirtattoos on each body diagram for the front and back of the bodyfor further image analysis. Another limitation was that most of
the study participants were women aged 20 to 30 years. This
reduced the heterogeneity of tattoo sizes and colors because inthis age group small tattoos, preferably black, seem to be themost common. As we had realized the similarity of exposure
during data collection, we then preferably invited people withlarge and colored tattoos. However, because of time constraints,
we were not able to fully make up for the preponderance ofsmall black tattoos, especially for the body schemes
questionnaire.
Of note, the software used for the web-based questionnaires did
not track time of questionnaire completion, which would havebeen helpful to judge the time burden to participants. However,
we did ask participants how much time they took approximately
to complete the questionnaire. Although none of the participantsmeasured the time, none of them perceived the questionnaire
as too long, regardless of their tattooed body surface.

Foerster et al
Finally, coefficients of the reliability measures for thecolor-specific analyses need to be interpreted with caution
because of the smaller subgroup sample size, which reduced
the possibility to detect smaller effects with sufficient statisticalpower. However, the scatterplots to visualize the relationshipbetween the self-assessed and validation measures somewhat
compensate for this shortcoming and may be more meaningful
here.

Conclusions
In this study, we developed the first questionnaire for theassessment of tattoo exposure in large-scale epidemiologicalstudies by comparing and validating 3 different units ofmeasurement for visually assessing tattoo exposure. The final
version of the EpiTAT consists of 21 items to measure visualand contextual factors of tattoo exposure. We recommend theuse of this validated instrument in future large epidemiologicalstudies to help combine data from different studies and facilitate
pooled analysis. The general overestimation of tattooed bodysurface area merits further research to identify potential
predictive determinants or patterns of overestimation for
calibration in dose-response risk analyses.

Acknowledgments
This study was supported by the French National Cancer Institute (2021-137) and by internal funding of the International Agency
for Research on Cancer.

Data Availability
Additional data are available from the corresponding author on reasonable request.

Disclaimer
Where authors are identified as personnel of the International Agency for Research on Cancer or the World Health Organization,
the authors alone are responsible for the views expressed in this paper; the views do not necessarily represent the decisions, policy,
or views of the International Agency for Research on Cancer or the World Health Organization.

Authors' Contributions
MF, IS, WB, and JS conceived and designed the work that led to the submission. MF and LD acquired and analyzed the data;
MF, LD, KE, WB, IS, MG, MZ, and JS interpreted the results. MF drafted the manuscript; LD, KE, WB, IS, MG, MZ, and JS
reviewed the manuscript; all authors approved the final version and agreed to be accountable for all aspects of the work in ensuringthat questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Conflicts of Interest
None declared.

Multimedia Appendix 1
Pictures used in the body schemes test questionnaire.
[PDF File (Adobe PDF File), 1206 KB-Multimedia Appendix 1]

Multimedia Appendix 2
The Epidemiological Tattoo Assessment Tool (EpiTAT), English version.
[DOCX File , 303 KB-Multimedia Appendix 2]

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

JMIR Form Res 2023 | vol. 7 | e42158 | p. 11(page number not for citation purposes)

JMIR FORMATIVE RESEARCH

Foerster et alMultimedia Appendix 3
Population profile; questionnaire version and color-specific plots of self-assessment versus validation measures: scatterplots andBland-Altman plots of tattooed body surface and coverage and scatterplots of assigned ranks; and color-specific scatterplots ofimage analysis versus validation measures.
[PDF File (Adobe PDF File), 1016 KB-Multimedia Appendix 3]

References
1.

2.

3.

4.

5.
6.

7.

8.

9.

10.
11.
12.
13.
14.
15.

16.

17.
18.
19.

Negi S, Bala L, Shukla S, Chopra D. Tattoo inks are toxicological risks to human health: a systematic review of theiringredients, fate inside skin, toxicity due to polycyclic aromatic hydrocarbons, primary aromatic amines, metals, andoverview of regulatory frameworks. Toxicol Ind Health 2022 Jul;38(7):417-434. [doi: 10.1177/07482337221100870][Medline: 35592919]
Hauri U. Inks for tattoos and permanent make-up – pigments, preservatives, aromatic amines, polyaromatic hydrocarbons
and nitrosamines. Swiss National Investigation Campaign. 2014. URL: https://www.kantonslabor.bs.ch/dam/jcr:d12e5456c71d-4e59-8f29-4a7d8c38d15d/Tattoo_PMU_2014_EN(UK).pdf [accessed 2022-12-07]
Battistini B, Petrucci F, De Angelis I, Failla CM, Bocca B. Quantitative analysis of metals and metal-based nano- andsubmicron-particles in tattoo inks. Chemosphere 2020 Apr;245:125667. [doi: 10.1016/j.chemosphere.2019.125667] [Medline:
31877461]
Wang X, Josefsson L, Meschnark S, Lind ML, Emmer Å, Goessler W, et al. Analytical survey of tattoo inks-a chemicaland legal perspective with focus on sensitizing substances. Contact Dermatitis 2021 Sep;85(3):340-353. [doi:10.1111/cod.13913] [Medline: 34089526]
Foerster M, Schreiver I, Luch A, Schüz J. Tattoo inks and cancer. Cancer Epidemiol 2020 Apr;65:101655. [doi:10.1016/j.canep.2019.101655] [Medline: 31836426]
Liard C, Munier S, Joulin-Giet A, Bonduelle O, Hadam S, Duffy D, et al. Intradermal immunization triggers epidermal
Langerhans cell mobilization required for CD8 T-cell immune responses. J Invest Dermatol 2012 Mar;132(3 Pt 1):615-625[FREE Full text] [doi: 10.1038/jid.2011.346] [Medline: 22170490]
Lehner K, Santarelli F, Vasold R, Penning R, Sidoroff A, König B, et al. Black tattoos entail substantial uptake ofgenotoxicpolycyclic aromatic hydrocarbons (PAH) in human skin and regional lymph nodes. PLoS One 2014 Mar
26;9(3):e92787 [FREE Full text] [doi: 10.1371/journal.pone.0092787] [Medline: 24670978]
Lehner K, Santarelli F, Penning R, Vasold R, Engel E, Maisch T, et al. The decrease of pigment concentration in red tattooedskin years after tattooing. J Eur Acad Dermatol Venereol 2011 Nov;25(11):1340-1345. [doi:10.1111/j.1468-3083.2011.03987.x] [Medline: 21349116]
Regensburger J, Lehner K, Maisch T, Vasold R, Santarelli F, Engel E, et al. Tattoo inks contain polycyclic aromatichydrocarbons that additionally generate deleterious singlet oxygen. Exp Dermatol 2010 Aug;19(8):e275-e281 [FREE Fulltext] [doi: 10.1111/j.1600-0625.2010.01068.x] [Medline: 20545755]
International Agency for Research on Cancer. Chemical Agents and Related Occupations: A Review of Human Carcinogens.
Lyon, France: International Agency for Research on Cancer; 2012.
Loomis D, Guha N, Hall AL, Straif K. Identifying occupational carcinogens: an update from the IARC Monographs. Occup
Environ Med 2018 Aug;75(8):593-603 [FREE Full text] [doi: 10.1136/oemed-2017-104944] [Medline: 29769352]
IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. Arsenic, metals, fibres, and dusts. IARC Monogr
Eval Carcinog Risks Hum 2012;100(Pt C):11-465. [Medline: 23189751]
International Agency for Research on Cancer. Some Aromatic Amines, Organic Dyes, and Related Exposures. Lyon, France:
International Agency for Research on Cancer; 2010.
Kluger N, Seité S, Taieb C. The prevalence of tattooing and motivations in five major countries over the world. J Eur Acad
Dermatol Venereol 2019 Dec;33(12):e484-e486. [doi: 10.1111/jdv.15808] [Medline: 31310367]
Warner FM, Darvishian M, Boyle T, Brooks-Wilson AR, Connors JM, Lai AS, et al. Tattoos and hematologic malignancies
in British Columbia, Canada. Cancer Epidemiol Biomarkers Prev 2020 Oct;29(10):2093-2095. [doi:10.1158/1055-9965.EPI-20-0515] [Medline: 32699076]
Barton DT, Zens MS, Marmarelis EL, Gilbert-Diamond D, Karagas MR. Cosmetic tattooing and early onset basal cell
carcinoma: a population-based case-control study from New Hampshire. Epidemiology 2020 May;31(3):448-450. [doi:10.1097/EDE.0000000000001179] [Medline: 32079835]
Nieuwenhuijsen MJ. Exposure Assessment in Environmental Epidemiology. 2nd edition. Oxford, UK: Oxford University
Press; 2015.
Nieuwenhuijsen MJ. Design of exposure questionnaires for epidemiological studies. Occup Environ Med 2005
Apr;62(4):272-214 [FREE Full text] [doi: 10.1136/oem.2004.015206] [Medline: 15778263]
German National Cohort (GNC) Consortium. The German National Cohort: aims, study design and organization. Eur J
Epidemiol 2014 May;29(5):371-382 [FREE Full text] [doi: 10.1007/s10654-014-9890-7] [Medline: 24840228]

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

JMIR Form Res 2023 | vol. 7 | e42158 | p. 12(page number not for citation purposes)

JMIR FORMATIVE RESEARCH
20.

21.

22.
23.

Foerster et al

Zins M, Bonenfant S, Carton M, Coeuret-Pellicer M, Guéguen A, Gourmelen J, et al. The CONSTANCES cohort: an open
epidemiological laboratory. BMC Public Health 2010 Aug 12;10:479 [FREE Full text] [doi: 10.1186/1471-2458-10-479][Medline: 20704723]
Schlich E, Schumm M, Schlich M. 3D-Body-Scan als anthropometrisches Verfahren zur Bestimmung der spezifischen
Körperoberfläche. Ernährungs Umschau. 2010. URL: https://www.ernaehrungs-umschau.de/fileadmin/Ernaehrungs-Umschau/
pdfs/pdf_2010/04_10/EU04_2010_178_183.qxd.pdf [accessed 2022-12-07]
Moore R, Waheed A, Burns B. Rule of Nines. Treasure Island, FL, USA: StatPearls Publishing; May 30, 2022.
Rhodes J, Clay C, Phillips M. The surface area of the hand and the palm for estimating percentage of total body surface
area: results of a meta-analysis. Br J Dermatol 2013 Jul;169(1):76-84. [doi: 10.1111/bjd.12290] [Medline: 23448271]

Abbreviations
AA-ICC: absolute agreement intraclass correlation coefficient
CA-ICC: consistency of agreement intraclass correlation coefficient
Constances: Cohorte des consultants des Centres d’examens de santé
EpiTAT: Epidemiological Tattoo Assessment Tool
ICC: intraclass correlation coefficient
NAKO: Nationale Kohorte
REDCap: Research Electronic Data Capture

Edited by A Mavragani; submitted 25.08.22; peer-reviewed by D Kriebel, M Kapsetaki; comments to author 27.09.22; revised version
received 03.10.22; accepted 03.10.22; published 11.01.23
Please cite as:
Foerster M, Dufour L, Bäumler W, Schreiver I, Goldberg M, Zins M, Ezzedine K, Schüz J
Development and Validation of the Epidemiological Tattoo Assessment Tool to Assess Ink Exposure and Related Factors in Tattooed
Populations for Medical Research: Cross-sectional Validation StudyJMIR Form Res 2023;7:e42158
URL: https://formative.jmir.org/2023/1/e42158
doi: 10.2196/42158
PMID:©Milena Foerster, Lucas Dufour, Wolfgang Bäumler, Ines Schreiver, Marcel Goldberg, Marie Zins, Khaled Ezzedine, Joachim
Schüz. Originally published in JMIR Formative Research (https://formative.jmir.org), 11.01.2023. This is an open-access article
distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR
Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on
https://formative.jmir.org, as well as this copyright and license information must be included.

https://formative.jmir.org/2023/1/e42158

XSL• FO
RenderX

JMIR Form Res 2023 | vol. 7 | e42158 | p. 13(page number not for citation purposes)