Photochemical &Photobiological Sciences

PAPER

Cite this: DOI: 10.1039/c3pp50041a

Received 6th February 2013,Accepted 17th June 2013

DOI: 10.1039/c3pp50041a

www.rsc.org/pps

Small doses from artificial UV sources elucidate thephoto-production of vitamin D

Richard McKenzie,*a Ben Liley,a Paul Johnston,a Robert Scragg,b Alistair Stewart,b

Anthony I. Reederc and Martin W. Allend

To clarify the relation between UV exposure and vitamin D status, 201 volunteers wore personal elec-

tronic UV dosimeters during daylight hours, to record their UV exposure over a 10 week period when

ambient UV levels were significantly less than the summer maxima. Blood samples to determine serum

25-hydroxyvitamin D3 [25(OH)D3] levels were taken at the end of week 4 and week 8. Participants were

then given a single full-body exposure of approximately 2 SED from one of four artificial UV sources with

different spectral outputs and a further blood sample taken at study completion, nominally week 10. The

artificial UV exposure reversed the mean seasonal decline in 25(OH)D3. Increases in 25(OH)D3 from week

8 to week 10 were related to total UV exposure, including the ambient sun exposures. These exposures

were weighted by the erythemal action spectrum and separately for three different action spectra for

pre-vitamin D production. For the erythema weighting function, 25(OH)D3 increased 1.78 ± 0.25 nmol

per litre per SED, a value consistent with other studies. Any differences due to age, BMI, gender, and skin

reflectance were not statistically significant. Ethnicity differences were the only significant factor, with

Asians producing the least vitamin D, and Maori the most. There was no statistically significant improve-

ment in consistency between sources for any of the three pre-vitamin weightings compared with that for

erythema. Further work is needed to verify which vitamin D action spectrum is most appropriate. Never-

theless, these small doses of UV from artificial sources were helpful in quantifying the relationship

between UV exposure and vitamin D status among the New Zealand population.

1. Introduction

There is increasing interest in the role of vitamin D in humanhealth, and the extent to which desirable vitamin D levels maybe achieved by exposure to UV radiation. The main study objec-tive of a recent study was to observe the relations between UVexposure and vitamin D status among the New Zealand popu-lation (Objective 1). Results from the main study are reportedelsewhere.1 A secondary objective of that study, which is ourfocus here, was to test the applicability of the accepted actionspectrum for endogenous vitamin D production (Objective 2).2

This was motivated by the observation that the seasonal varia-bility of vitamin D production at mid-latitudes is at variance

with expectations based on the published action spectrum forpre-vitamin D production.3

2. Methods2.1. Study design

The data in this report come from a sub-sample of 201 volun-teers recruited as part of a larger sample of 506 people toquantify the association between personal UV exposure andvitamin D status.1 Participants were recruited from Aucklandand Dunedin cities, and for logistical reasons, recruitment wasspread over two calendar years: 2008 and 2009. For Objective1, each participant provided data collected over 8 weeks(excluding the peak summer UV period) during which per-sonal UV exposure and change in serum 25-hydroxyvitamin D3

[25(OH)D3] were monitored. Volunteers for Objective 2 wererandomly assigned to receive a single full-body UV exposure ofapproximately 2 SED from one of two previously calibrated arti-ficial UV sources in each city. These sources, selected to ensurea broad diversity in spectral irradiances (described later), weredesignated booth A and booth B for the Auckland participants,and bed 1 and bed 2 for Dunedin participants. For the small

aNational Institute of Water and Atmospheric Research, NIWA Lauder, Central Otago,

New Zealand. E-mail: richard.mckenzie@niwa.co.nz; Fax: +64 03 4473348;

Tel: +64 03 4400429bSchool of Population Health, University of Auckland, Auckland, New ZealandcCancer Society Social and Behavioural Research Unit, Department of Preventive and

Social Medicine, Dunedin School of Medicine, New ZealanddMacDiarmid Institute for Advanced Materials and Nanotechnology, University of

Canterbury, Christchurch, New Zealand

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UV doses administered, the vitamin D production attributableto UV exposure should be approximately proportional to thepre-vitamin D weighted irradiance to which participants areexposed, after controlling for any effects due to differences inthe population samples exposed to each source. We comparethese sensitivities for several action spectra (Fig. 1) to deter-mine which gives the most consistent results. The study wasfunded by the Health Research Council of New Zealand (NZ),with ethical approval from the NZ Multi-Region committee(MEC/07/10/142).

2.2. Participants

2.2.1. Selection criteria. In the overall study (506 partici-pants), two thirds of participants were from Auckland (36.85°S), and one third from Dunedin (45.89°S), representing thenorthern and southern regions of New Zealand, respectively.Approximately equal numbers were selected from each of thefour main ethnic groups: Maori, European, Pacific (comprisingSamoan, Cook Island Maori, Tongan, and ‘other’ Pacific) andAsian (comprising Indian, Chinese and ‘other’ Asian). There

was an approximately equal distribution within ethnic groupsby sex and age groups, 18–85 years.

In the sub-sample discussed here (206 participants), whereindividuals were randomly assigned one of two different artifi-cial UV sources at each site, the distributions of age, ethnicity,BMI that were exposed to each source were similar. However,there were significant differences in the ethnic diversity foreach as discussed further below. Recruitment for these partici-pants began mid February (day 48) and ended early September(day 253) to ensure that the study period excluded the heightof summer when peak, clear sky UV in New Zealand can beextreme.

2.2.2. Exclusions. Participants were excluded if identifieditems on pre-determined lists of photosensitising medicines,diseases or dietary supplements had the potential to affectvitamin D status. In total, 206 participants completed the10-week study, but 3 were excluded because their ethnicity wasAfrican, not one of the target ethnicities; one was excludedbecause the date of exposure to an artificial UV source was notrecorded; and one was excluded because their recorded serum25(OH)D3 at week 8 was zero and clearly incorrect. Overall, 201were included, as distributed in Table 1.

We investigated other exclusion criteria, such as excludingparticipants who received very high ambient UV levels, orunexpectedly large differences between the week 4 and week 8blood assays, or excluding participants for whom the timeperiod between the sunbed exposure and the blood test wasmore than 2 weeks, or less than 2 days. These restrictions didnot materially change the results, or appreciably change theoverall patterns. The only exclusion criterion that approachedsignificance was when the sample was restricted to partici-pants for whom the maximum initial 25(OH)D3 measured atweek 4 was less than 50 nmol per litre (to restrict to partici-pants close to or less than the mean value in the sample),80 nmol per litre, and 100 nmol per litre (to omit extreme out-liers) respectively. A previous study had shown non-significantincreases in 25(OH)D3 for participants with initial 25(OH)D3

values greater than 80 nmol per litre.7 However, the numbersof participants was small in that study, and the present studyshowed a smaller dependence on initial concentrations. Theanalysis reported considers all of the 201 participants shownin Table 1.

2.3. Baseline interview, measurements and questionnaire

At baseline, age, self-defined ethnicity, height and weight(used to calculate the body-mass index (BMI)), and skin reflec-tance were recorded. The latter was measured at three sites(inner arm, outer arm, and forehead) using a Datacolor Checkspectrophotometer, and results were recorded in terms of theIndividual Typology Angle (ITA1, ITA2, and ITA3 respecti-vely).8,9 The fairest skins have ITA values that approach 90,whereas the darkest skins have ITA values less than zero.

Participants provided answers to questionnaire items aboutsun exposure patterns, dietary preferences and medical con-ditions. Each day of the study participants completed a dailydiary to indicate for three time periods (up to 11 am, 11 am to

Fig. 1 Action spectra investigated, plotted on a linear y-axis (upper panel), andlogarithmic y-axis (lower panel). Note that the Bolsee spectrum4 has beendivided by 0.277 to renormalize to unity at 298 nm to facilitate comparisonwith the CIE2,5 and the Queensland University of Technology (QUT) spectrameasured by Olds.6

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4 pm, after 4 pm) clothing worn and sunscreen use when theywere outdoors, and any travel further than 100 km from theirusual place of residence. The dietary information collected wasrestricted to recording the intake of foods that are known tocontain vitamin D,10 and are commonly consumed in NewZealand. Participants thus diarised their weekly consumptionof four varieties of canned fish (tuna, mackerel, salmon andsardines), and four other foods (fresh salmon, lamb fry, eggs,and fortified milk). From these, the daily intake of vitamin Dwas estimated.11 It was found that the mean dietary intake wasless than 50 IU, and fewer than 5% of the participants receivedmore than 500 IU of vitamin D per day. Dietary data were notused further in the present analysis because (a) there was awide range in estimated vitamin D for a given serving of eachfood type, (b) the status of vitamin D could have been signifi-cantly influenced by diet in only 1 or 2 of the ∼200 partici-pants, (c) of these, the changes in 25(OH)D3 reported would beinfluenced only in those for whom dietary input changedduring the period of the study, and (d) in the few cases testedwhere the calculated dietary consumption was largest, thefood consumption reported looked unrealistic. We note thatsubsequent studies have shown that dietary intake may bemore important than previously thought.12,13

There were approximately twice as many participants inAuckland as in Dunedin. The overall proportion of femaleswas 61%. However, that proportion varied markedly betweensubsets. The age and BMI distributions were similar to thosein the full sample of the study. However, there were significantdifferences in skin reflectance, with subsets 2, 4, and 7 havingsignificantly smaller ITA values, due to their increased pro-portion of non-Europeans with darker skin (Table 2). The

ethnic spread also differed significantly between sub-sets, inparticular, between the Auckland and Dunedin participants.The distribution among the four main ethnic groups in eachyear of the study is summarised in Table 2. The dominantethnicity for each subset is highlighted in bold face type.There was a greater proportion of Europeans in Dunedin, anda relatively higher proportion of Asians among the Aucklandparticipants. Because there is a wide variety of skin typeamong the Asian ethnic category, we further subdivided thoseinto their constituent categories (Chinese, Indian, and otherAsian). In Auckland the Asian subsets are dominated byIndians, whereas in Dunedin they are dominated by Chinese.In fact, in Dunedin there was a complete absence of Indians.

It has recently been shown,1,14 that of the variables testedin this population sample, ethnicity is the strongest determi-nant of vitamin D status. Compared with this, the skin reflec-tance (ITA), and the BMI have only minor effects. It thereforefollows that attempts to determine the optimum action spec-trum must include allowances for differences between thesubsets arising from ethnicity differences.

2.4. Procedures

The sequence for administration of study measures for the 201participants undertaking the full 10-week study is summarisedin Table 3. Diaries of clothing records were also collectedduring the weekly visits.

2.5. UV from sunlight

UV exposure was measured by electronic personal dosi-meters15,16 which sampled erythemally-weighted UV irradiancereceived on the outer wrist at 8 second intervals during

Table 1 Statistics for subsets, separated by UV source and year, of participants in Objective 2 of the study (DoY = day of year)

Subset City UV source Year n % Female Mean age Mean BMI Mean ITA1 Mean ITA2 Mean ITA3 Mean DoY (week 10)

1 Ak Booth A 2008 35 74 45 28 47 20 29 2282 Ak Booth A 2009 30 57 56 29 38 5 11 2383 Ak Booth B 2008 32 59 46 29 49 22 28 2274 Ak Booth B 2009 37 46 55 28 35 8 9 2345 Dn Bed 1 2008 20 55 39 29 45 21 21 2036 Dn Bed 1 2009 13 69 46 28 46 24 27 2047 Dn Bed 2 2008 18 72 41 27 36 13 11 2368 Dn Bed 2 2009 16 44 44 30 42 20 24 212

Table 2 Illustrating differences in ethnic diversity between participants in each subset (exposed to the different UV sources each year of the study). The dominantethnicity for each subset is highlighted in bold face type. Numbers in parentheses represent the percentage of that ethnicity compared with the total for all ethnici-ties that used that UV source in each year of the study. The Asian subsets are represented in the last three columns (in italics)

Subset City UV source Year n European Maori Pacific Asian Asian Indian Asian Chinese Asian other

1 Ak Booth A 2008 35 13 (37) 9 (26) 5 (14) 8 (23) 5 (14) 3 (8) 0 (0)2 Ak Booth A 2009 30 4 (13) 9 (30) 8 (27) 9 (30) 9 (30) 0 (0) 0 (0)3 Ak Booth B 2008 32 12 (38) 8 (25) 2 (6) 10 (31) 6 (19) 3 (9) 1 (3)4 Ak Booth B 2009 37 4 (11) 7 (19) 7 (19) 19 (51) 17 (46) 1 (3) 1 (3)5 Dn Bed 1 2008 20 9 (45) 6 (30) 2 (10) 3 (15) 0 (0) 2 (10) 1 (5)6 Dn Bed 1 2009 13 6 (46) 4 (31) 1 (8) 2 (15) 0 (0) 2 (15) 0 (0)7 Dn Bed 2 2008 18 4 (22) 4 (22) 2 (11) 8 (44) 0 (0) 6 (33) 2 (11)8 Dn Bed 2 2009 16 8 (50) 5 (31) 2 (13) 1 (6) 0 (0) 0 (0) 1 (6)

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daylight hours and have been used previously in studies toestimate personal exposures to sun burning UV.17,18 The elec-tronic dosimeters were specifically designed to record personalUV exposures with high temporal resolution compared to stan-dard chemical radiation badges. The resulting data can beeasily integrated to give received doses over selected time inter-vals but significantly also allows non-compliant behaviour tobe identified. This is possible as the temporal data fromnormal outdoor behaviour has a recognizable pattern in thatdosimeter readings from sunlight fluctuate significantly withthe dosimeter orientation when the UV is sampled, but withinknown parameters limited by the available ambient UV. In thecurrent study, this enabled non-compliant situations, forexample when the dosimeter had been removed by a partici-pant and/or left lying exposed to sunlight, to be identified.Prior to the study, each dosimeter was calibrated directlyalongside research-grade instruments with calibrations thattraceable to The USA’s National Institute of Standards andTechnology (NIST) as described previously.12 Here the dosi-meters were calibrated in terms of erythemally weighted UV,but a radiative transfer model was used to convert the erythe-mally weighted values into UV exposures relevant to the con-version of 7-dehydrocholesterol (pro-vitamin D) in the skin topre-vitamin D, the first step in serum vitamin D (25(OH)D3)production. The conversion factor is a function of the solarzenith angle and the column amount of ozone in the atmos-phere. Previous studies had shown that the wrist is a represen-tative site for UV exposure,19 so dosimeters were mounted onstraps similar to watchstraps. Participants were asked to wearthe dosimeter on the wrist throughout the study period when-ever they were outside.

As only approximately 100 dosimeters were available, it wasnecessary to spread the study over two years. To minimisepotential data losses (e.g., due to dosimeters being lost), datawere uploaded during the weekly interviews. Because there wasa large number of interviews (over 4000) during the course ofthe full study, and it took several minutes to upload data fromeach dosimeter; the usual procedure was to issue participantswith re-initialised replacement dosimeters that had been used

by previous participants, and to upload data after the inter-view. Thus dosimeters were usually switched at weekly inter-vals. At study completion, all data were processed to produceSED output using calibrations against research grade UV-sensors maintained by NIWA at Lauder, Central Otago.

Dosimeter readings from sunlight fluctuate greatly depend-ing on orientation when UV is sampled, but within parameterslimited by available UV. Occasionally, it was clear from thedata that a dosimeter had been left lying indoors. Such occur-rences, and other data affected by electronic interference wereexcluded, and missing data interpolated as describedelsewhere.20

Ambient UV irradiances from each site were derived usingthe NIWA UV Atlas21 for quality control and assessment of theeffects of cloud and personal behaviour on UV exposure. Theproducts used comprise hourly means of erythemally-weightedUV and vitamin-D weighted UV irradiances impinging on ahorizontal surface, both including and excluding the effects ofcloud.

With 8 second sampling, 6 am to 10 pm each day for aperiod of 8 to 10 weeks, the total number of data pointsacquired can exceed 500 000 per participant (i.e., over200 million UV dosimeter data points in the entire study).When correctly initiated, over 95% of the data points passedquality assurance tests, but set-up difficulties during the firstyear of the study produced some missing data, particularly inAuckland. However, the overall data acceptance rate wasapproximately 80%. Missing data were interpolated using aprocedure described elsewhere.20

The quantitative relationship between erythemally-weightedirradiance5 and other biological weightings (such as vitamin Dweighted irradiances) depends on the wavelength-dependenceof the source spectrum.22 For solar spectra, the main determi-nant of spectral shape are the solar zenith angle (SZA = 90° –

solar elevation angle) and the total amount of ozone (TOZ) inthe atmosphere. A radiative transfer model was used to pre cal-culate look-up tables of correction factors as functions of SZAand TOZ to convert erythemally weighted irradiances toweighted irradiances for three possible action spectra for the

Table 3 Administration of measures throughout full study

Studyweek

Personal UV dosimetermeasurement period Measures obtained

0 Baseline interview and measurements, dosimeter issued1 Period 1 Dosimeter data uploaded and dosimeter replaced2 Dosimeter data uploaded and dosimeter replaced3 Dosimeter data uploaded and dosimeter replaced4 Dosimeter data uploaded 1st blood sample5 Period 2 Dosimeter data uploaded and dosimeter replaced6 Dosimeter data uploaded and dosimeter replaced7 Dosimeter data uploaded and dosimeter replaced8 Dosimeter data uploaded and dosimeter replaced 2nd blood sample9 Period 3 Full-bodya artificial UV exposure(s) soon after blood sample provided,

dosimeter data uploaded and dosimeter replaced10 Dosimeter data uploaded 3rd blood sample

aUnderwear was worn, which represents 6% skin coverage for males and 11% for females.

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production of vitamin D.2,4,6 Adjustments were made to esti-mate UV exposures, taking into account clothing and sun-screen usage, as recorded in the diaries.

2.6. UV from artificial sources

Four artificial UV sources were used in the study: two each inAuckland and Dunedin. Those in Auckland were stand-upphototherapy booths at a dermatology clinic, whereas those inDunedin were commercial sunbeds, typically used for cosmeticpurposes.

The Auckland phototherapy booths are designated booths Aand B, depending in whether they primarily emitted UV-A orUV-B radiation. The UV-A chamber (model Daavlin Spectra305/350) comprised 36 tubes of type “Philips F 72 T12 BL-HO”,and the UV-B chamber (model Daavlin Spectra 726-SP-2X)comprised 20 tubes of type “Philips TL 100W/01-FS72”. TheDunedin artificial UV sources were designated as beds 1 and2. Users lying on these beds were irradiated from above andbelow. Both beds emitted primarily UV-A radiation. Bed 1 wasa Hapro Luxura model, with 26 “Hapro 100 W R” tubes and aface tube. Bed 2 was an older, unlabelled sunbed fitted with 24newly-purchased “100 W Cosmedico brilliant” tubes. It alsoincluded a single smaller tube at one end of the lid to irradiatethe face.

The mean spectral irradiance from each UV source wasdetermined from multiple measurement sites and orientationswithin each solarium at the outset and completion of thestudy as described previously.23,24 Spectral irradiances andweighted irradiances from the four sources are compared withsummer and winter sunlight in Fig. 2 and Table 4, respectively.The stability of the sources was also monitored during thestudy period, and found stable to within ±7%.23 Participantswere exposed for fixed periods of time so that they received atotal full body UV dose of approximately 2 SED (1 standarderythemal dose (SED) = 100 J m−2 of erythemally weighted UV).The increases in 25(OH)D3 were smaller than expected, so inthe second year of the study, we changed the protocol so thatthe Dunedin participants received two such doses, approxi-mately 1 week apart, in an attempt to improve the “signal tonoise ratio” (i.e., the accuracy in determination of the smallchange in vitamin D for a given UV dose). Because we wereconcerned about unexpected consequences of this change,such as possible effects due to the decreased time between theUV exposure and the final blood test, the protocol wasunchanged in Auckland where the majority of participantswere located. Participants were instructed to wear only theirunderwear during the exposures, which resulted in effectively∼94% of full body exposure for males, and 89% for females.Irradiances were scaled down by these factors to account forthis coverage. Because not all participants wore their dosi-meter, the data from artificial sources was excluded from theprocessed personal UV data. The exposures used (Table 5) werethose calculated from the calibration results for each bed, asdiscussed previously.24

Calculated exposure doses for each artificial UV source interms of the 4 weighting functions tested (see Fig. 1) areshown in Table 5.

2.7. Serum vitamin D

Blood samples were taken in study weeks 4, 8 and 10 after thebaseline interview (nominally). All three samples from eachparticipant were assayed in the same batch to avoid inter-batch errors in the differences. Vitamin D status is reported interms of the serum concentrations of 25(OH)D3 measuredusing liquid chromatography-tandem mass spectrometry(ABSciex API 4000, CV 10%).25,26

Fig. 2 Comparison of sources. Mean spectral irradiances of the four artificialUV sources compared with sunlight at 45°S near noon at the summer andwinter solstices.

Table 4 Measured parameters from the artificial UV sources compared with noon sunlight at 45°S at the summer and winter solstices. Measurement uncertainties(95% confidence limits) are ±15% for the artificial sources and ±5% for sunlight

Parameter (unit) Booth A Booth B Bed 1 Bed 2 Winter sun Summer sun

UV-A (315–400 nm, W m−2) 188.0 15.2 105.8 131.4 18.0 61.6UV-B (280–315 nm, W m−2) 1.83 55.4 0.708 2.03 0.180 2.07UV index (UVI) 15.6 158 6.8 13.9 1.0 11.3UVEry

5 (W m−2) 0.391 3.94 0.17 0.347 0.026 0.282UVVitD

2 (W m−2) 0.455 8.97 0.181 0.485 0.032 0.567UVVitD/UVEry 1.16 2.27 1.06 1.40 1.22 2.01T2SED (minutes) 8.53 0.85 19.62 9.62 128.14 11.82Exposure time (minutes) 9.00 0.80 19.00 11.00 n/a n/a

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2.8. Analysis

We analysed changes in 25(OH)D3 from week 8 to week 10 thatincluded the controlled artificial UV exposures, compared withchanges for the reference period (week 4 to week 8) in whichthere were no exposures to artificial UV sources. The appli-cation of different weighting functions was investigated to seewhich best matched the data. We investigated the effect ofexclusions based, for example, on initial 25(OH)D3 levels, highambient UV exposure, short period between UV exposure andblood take. The latter was considered because, although thenominal period between the solarium exposure and the finalblood test was 14 days, there was a wide variability in practise.In one case, the length of time between the last solariumexposure and final blood test was 49 days. Excluding thatperson, the maximum elapsed time was 25 days. In study yeartwo, most Dunedin participants received two sunbedexposures, one week apart, so the length of time was typicallyshorter, which may have potentially affected the resultantbuild-up of 25(OH)D3. For these, the average elapsed time wasone week, but in one case, it was only 1 day.

None of these exclusions had significant effects comparedwith using the full study group. We also investigated morecomplex relationships that included effects of changes in 25(OH)D3 over both periods, and included estimated effects ofrise times and decay times for the production and dissipationof 25(OH)D3. However, because the changes in 25(OH)D3 wererelatively small compared with the variability between partici-pants, measurement uncertainties in these latter attemptsescalated beyond useful limits.

Linear regression was used to investigate the relationshipbetween the UV exposures and the changes in 25(OH)D3, aftercontrolling for the effects of differences between the variouspopulation groups in the study. The model included the fourmain ethnic groups, year (since mean 25(OH)D3 doses differedbetween the two study years), age, sex, BMI, average level of25(OH)D3, skin reflectance for unexposed and exposed areas(i.e., the ITA at inner and outer arm), ambient UV exposures asmeasured by the personal UV dosimeters, and exposures fromthe artificial UV sources. The model was applied separately foreach of the 4 different weighting functions tested.1,3–5

However, it was found that the only statistically significantfactor (p < 0.05) affecting changes in 25(OH)D3 was the UVexposure.

3. Results3.1. UV exposures

The upper two curves in Fig. 3 show the ambient UV dose perweek at each site during the full period of study. The corres-ponding UV doses received by each participant are shown bythe joined lines in the lower portion of the figure. These latterpoints have been scaled down by clothing factors to representthe equivalent full-body UV exposure, since that is the relevantquantity for maintaining vitamin D status. Typically, this cloth-ing factor is less than 0.2 (i.e., typically 80% of total skinsurface is covered by clothing). This scaling implicitly assumesthat all areas of skin are equally effective in producing vitaminD, an assumption which may not be valid.27 It also assumesthat the threshold dose for any non-linearities in vitamin Dproduction is independent of the source spectrum. Since someof this non-linearity results from the production of otherisomers that have different absorption spectra,28 this assump-tion too may be questioned. Interestingly, despite Dunedin’scooler climate, the mean clothing cover was slightly lower forDunedin participants than for Auckland participants, tendingto offset the effect of the large geographic differences in avail-able UV – especially in winter – between the two sites.

In the first two periods, before the artificial UV exposureintervention, personal equivalent full-body UV exposures weregenerally less than 1% of the ambient UV exposures. Typically,they were less than ∼0.5 SED per week, resulting in cumulativedoses over the nominal 4-week periods of significantly lessthan the 2 SED artificial UV dose. In period 3, which includedthe UV exposures from the artificial sources, doses are typicallyan order of magnitude greater, but are still two orders of mag-nitude less than New Zealand’s ambient summer UV, and 1order of magnitude less than winter UV. However, there areseveral outliers, particularly in late summer (DoY < 100) and

Table 5 Erythemally-weighted and pre vitamin D weighted UV exposuresadministered per session for each artificial UV source. Note that for Dunedin par-ticipant in 2009, there were generally two solarium sessions

Artificial UV source

Erythemallyweighted dose

Pre-vitamin D weighteddose according to threeweighting functions tested

SED5 SDD2 SDD′6 SDD′′4

Booth A 2.11 2.49 0.787 0.283Booth B 1.89 4.29 0.584 0.197Bed 1 1.94 2.06 0.807 0.307Bed 2 2.29 3.21 0.760 0.282

Fig. 3 Joined lines show the personal equivalent full-body UV doses per weekfor each period received by each participant. Closed symbols are used for partici-pants exposed to the predominantly UV-A sources (i.e., booth A, and beds 1 and2), and open symbols are used for the predominantly UV-B source (booth B).The thick black line segments in the centre show the median exposures in eachperiod respectively. Upper small crosses represent the corresponding ambientUV doses for the same periods.

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late spring (DoY > 250), with high ambient exposures such thatthe total exposure during period 3 was sometimes less than inperiod 2. For example, the group of 4 in Auckland who beganthe study around day 250.

3.2. Changes in 25(OH)D3

Changes in vitamin D status for each participant through timeare shown in Fig. 4. Symbols are plotted at the times of bloodcollection (nominally at 4-week, 8-week, and 10-week). Prior tothe artificial UV exposure, most of the participants vitamin Dstatus follow the expected seasonal variation in the meanvalues for New Zealanders as shown by the thick green line.29

Vitamin D status is generally highest for the third bloodsample, taken after the intervention (an equivalent full-bodyexposure to approximately 2 SED from the artificial UVsources).

3.3. Relationship between UV exposure and 25(OH)D3

Corresponding changes in vitamin D status as a function ofcumulative equivalent full-body UV exposure are shown inFig. 5, where the equivalent full body exposure was deduced byadjusting the measured doses downward to correct forclothing.

Again there is a wide variability among participants both inabsolute levels, doses, and responses. In some cases, serum 25(OH)D3 decreases in spite of significant doses of UV, showingthat other factors must also be important in maintainingvitamin D status. The mean changes from week 4 to week 8 ofthe study (first black line segment) are slightly negativebecause most participants were recruited during the decreas-ing phase of the seasonal changes (refer to green line inFig. 3). The mean cumulative equivalent full body exposure

from week 4 to week 8 was 1.9 SED, which implies that equi-valent full-body UV exposures less ∼0.5 SED per week areinsufficient to maintain the mean vitamin D status for thispopulation. This value is in good agreement with the thresholdderived previously from the full study population sample of501 participants.1 However, during the 2-week interventionperiod from week 8 to week 10 of the study (second black linesegment), the supplemental UV dose of ∼2 SED from artificialsources was sufficient to more-than-compensate for the meanseasonal reduction. During this period, the mean increase in25(OH)D3 for the 201 participants is 1.78 ± 0.25 nmol per litreper SED. These mean changes are consistent with thosededuced previously from the cumulative effect from muchlarger UV doses from multiple exposures to booth A and boothB administered over a 12-week period (green line).30

Fig. 6 shows scatterplots of the changes in 25(OH)D3 asfunctions of the erythemally-weighted UV dose, along with alinear fit to those changes. The upper panel shows thechanges in the reference period (week 4 to week 8) in whichthere were no artificial UV exposures. The lower panel showsthe changes between week 8 and week 10 that included in theartificial UV exposure interventions at the start of the period.For small doses, such as those administered, we have con-strained the regression fit to pass through the origin. The dis-tribution of UV exposures was non-normal, so they have beenplotted on a logarithmic axis, which distorts the appearance ofstraight line fit. Because ambient exposures are small, thereare no significant changes in 25(OH)D3 in the referenceperiod. However, from the intervention period we deduce,from the fitted gradient, that the 25(OH)D3 increases byapproximately 1.36 nmol per litre per SED of full-body UVexposure. The sensitivity deduced by this fit is lower than that

Fig. 5 Vitamin D status as a function of cumulative UV exposure for each par-ticipant, for the periods shown in Fig. 4. Closed symbols are used for participantsexposed to the predominantly UV-A sources (i.e., booth A, and beds 1 and 2),and open symbols are used for the predominantly UV-B source (booth B). Theblack line segments in the centre show the mean changes from the means ofweek 4 to week 8, and from week 8 to week 10 respectively. The smooth thickgreen line shows the changes in 25(OH)D3 as estimated for large UV doses frombooth A and booth B30 (i.e., Δ25(OH)D3 = 10 ln(SED), with offset adjusted toensure the initial value intercepts the initial mean value).

Fig. 4 Changes in vitamin D status over time per participant compared withmean values for New Zealand.29 Closed symbols are used for participantsexposed to the predominantly UV-A sources (i.e., booth A, and beds 1 and 2),and open symbols are used for the predominantly UV-B source (booth B). Thesmooth thick green line shows the seasonal changes in vitamin D statusexpected for the New Zealand population without the intervention.29 The thick-est black line segments in the centre show the mean changes in the entirepopulation group from week 4 to week 8, and week 8 to week 10 periodsrespectively. The first segment follows the green curve, but diverges above thatcurve for the intervention period.

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derived from the simple means above (1.78 nmol per litre perSED) without constraining the fit to pass through the origin,but the difference is not statistically significant when uncer-tainties from each method are considered. Correspondingplots for the three vitamin D weighting functions consideredshowed similar correlations with y-intercepts close to zero, butdifferent gradients as discussed below. From those figures (notshown) there is no obvious advantage from any particularweighting function.

3.4. Separation of mean changes

Mean changes in 25(OH)D3 status (ΔD) between the week 4and week-8 blood sample were statistically insignificant. Forthe Auckland population especially, there is a tendencytowards reduction in 25(OH)D3 over this period. The reasonsfor this are not clear. However from week-8 to week-10, whichincluded the controlled artificial UV exposure, there were sig-nificant increases for all subsets.

Ambient exposures per day – converted to equivalent fullbody exposure values using the diary clothing data – were

similar for all three periods, with slightly larger exposures forthe Auckland participants. The mean total equivalent full bodyexposure for UV period 3, which included the interventionexposures, was between approximately 3 SED (1 SED fromambient UV, and 2 SED from artificial UV). Larger doses occurfor Dunedin in 2009 when there were usually two solariumexposures. The mean period between the exposure to the artifi-cial UV source and the final blood test was 13 days, but for theDunedin participants in 2009, when there were generally twosolarium exposures, the means was 8 days. In all cases, theartificial UV exposure was the dominant component of themean total doses for period 3.

Mean values, separated into various categories (e.g., by sex,ethnicity, site, study year, UV source allocation) are shown inTable 6. Here the UV doses in each period represent theambient UV received, as measured by the dosimeters, adjustedto full-body equivalent exposure. They do not include the con-trolled artificial UV dose, which was approximately 2 SED (seeTable 5). Exposures in period 3 (2 weeks) are about half ofthose in either of the first two periods (4 weeks each). The nextthree columns show the mean 25(OH)D3 at the end of eachperiod. The final two columns show the change in 25(OH)D3

from week 8 to week 10, and the deduced sensitivity, definedas the change in 25(OH)D3 per SED of equivalent full bodyerythemally-weighted5 exposure including the exposure fromthe artificial UV sources. The uncertainty shown in the latter isthe standard error of the mean.

The lower portion of Table 6 shows effects of the differentartificial UV sources, which will be discussed later. Focusingfirst on the entries in the upper portion of the table, wherethere is no separation by UV source, we find that in each casethe changes in 25(OH)D3 and the deduced sensitivities ofserum 25(OH)D3 to UV exposures are comparable between thedifferent subsets. Apart from the small ‘Asian/Other’ category,none of the deduced sensitivities differ significantly from thepopulation mean of 1.78 nmol per litre per SED. However,there is a suggestion for lower values for Asians, who also hadthe lowest BMI and low ITA values. Interestingly, slightlygreater values were found for Maori and Pacific Islanders, forwhom BMI values were also significantly larger. The skin ITAwas lowest for this group. However, the number of PacificIslanders taking part in this part of the study was relativelysmall. There were no significant differences with age, sex, BMI,or ITA. As noted above, there were significant differences inethnicity in the participants exposed to each artificial source,but these results suggest that should not have a major effect.Values were slightly larger among Dunedin rather than Auck-land participants (though the differences were statisticallyinsignificant). There were no statistically significant differ-ences in sensitivities between the two study years.

3.5. Separation of mean changes by artificial UV exposureand weighting function

The lower portion of Table 6 shows mean values for partici-pants exposed to each of the artificial UV source, and forvarious subsets of those. Sensitivities for these and for all

Fig. 6 Changes in 25(OH)D3 as functions of erythemally-weighted UV dose.Upper panel: from week 4 to week 8 (the reference period). Lower panel: fromweek 8 to week 10 (the intervention period which included the artificial UVexposures). The solid red lines are linear fits through the origin, and dashed redlines are the 95% confidence limits to the fits.

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other subsets considered are represented graphically in the leftpanel of Fig. 7, where data separated by artificial UV source areshown below the dashed line.

Sensitivities were also calculated using 3 different assumedweighting functions for vitamin D production,2,4,6 as shown inthe other three panels of Fig. 7 (see figure caption). In thesecases, sensitivities are defined as the change in 25(OH)D3 perSDD† of equivalent full-body UV exposure. Differences betweenthese weighting functions lead to large differences in deducedsensitivities, especially for the Bolsee weightings, which aremuch smaller in the wavelength range of interest (see Fig. 1).Patterns of sensitivities are very similar for the Olds and theBolsee weighting functions. They differ only in a scale factor,with the latter all being approximately three times larger.

As discussed above, differences in ethnicity may be impor-tant, so we also show corresponding values for the largestethnic subset; those who identified themselves as European.There were a similar number of Asians, but those exposed tothe artificial UV sources Auckland (booth A and B) were mainlyIndian, whereas those exposed to the artificial sources inDunedin (bed 1 and 2) were mainly Chinese (none wereIndian). Indians had the lowest mean skin reflectance, but the

lowest sensitivities were for Chinese. The sensitivity represent-ing Asians/Other (i.e., not Indian or Chinese) is much largerthan the other subsets, and has been clipped from the rightpanel. There were only 5 in that category. Their skin reflec-tances were greater than for Indians, and more comparablewith Chinese. These sensitivities by skin reflectance are notconsistent with earlier research,32 and are more suggestive ofan ethnic effect rather than skin reflectance effect.

We now focus on differences in deduced sensitivitiesderived from each of the 4 artificial UV sources (i.e., the last8 lines in Fig. 7). We considered that the “best” action spec-trum would be that which gave the most consistent valuesbetween these disparate artificial UV sources, as evidenced byunexplained differences from the mean values shown by thevertical dotted lines in each panel. Unfortunately, the resultswere largely inconclusive. Over the whole population sampled,the deduced sensitivities to erythemally-weighted UV fromeach artificial UV source do not differ significantly from thesemean values. However, there are apparently significant differ-ences for the three vitamin D weightings. For example, usingthe CIE weighting function, the deduced sensitivity seems tobe less than the mean for bed B, but greater than the mean forbed 1. For the other two weighting functions, the results aretoo low for bed A. However, when restricted to just the Euro-pean subset (last 4 entries in Fig. 7), it appears that none ofthe weighting function tested gave consistent results for allfour beds. While these differences may not be significantwhen systematic uncertainties are included, they do neverthe-less give cause for concern regarding the applicability of that

Table 6 Summary of mean values separated by sex, ethnicity, site, year of study, and artificial UV source. The final two columns represent the change in 25(OH)D3

from week 8 to week 10, and the deduced sensitivity defined as the change in 25(OH)D3 per SED of equivalent full body exposure

Subset n Age BMI ITA3uv_p1 uv_p2 uv_p3 VitD VitD VitD ΔVitD ΔVitD/ΔUVSED SED SED Wk04 Wk08 Wk10 nmol l−1 nmol l−1 per SED

All 201 48 29.0 20.3 2.5 1.9 1.0 45 44 49 5.0 1.78 ± 0.25Male 79 50 29.0 10.6 2.9 2.0 1.0 44 42 47 4.9 1.66 ± 0.37Female 122 46 29.0 26.6 2.2 1.8 1.0 46 44 49 5.1 1.86 ± 0.35Age > median 103 61 29.2 18.7 2.3 1.7 0.7 48 47 52 4.9 1.94 ± 0.29BMI > median 101 49 33.7 15.6 2.0 1.9 1.1 40 39 44 5.3 1.88 ± 0.30Skin ITA > median 94 46 27.4 35.0 2.7 2.3 1.1 49 49 53 4.9 1.68 ± 0.42European 60 51 26.5 37.9 3.2 2.3 1.0 57 55 60 4.4 1.35 ± 0.46Maori 52 43 31.1 15.8 3.5 2.7 1.2 48 45 52 6.6 2.38 ± 0.58Pacific Islander 30 47 33.6 9.6 2.2 1.5 1.0 43 42 49 6.6 2.18 ± 0.47Asian 59 48 27.4 11.8 1.0 0.9 0.7 32 31 34 3.5 1.49 ± 0.46Indian 45 52 27.9 5.2 1.2 1.1 0.8 31 29 32 2.7 1.15 ± 0.49Chinese 9 35 24.6 36.3 0.5 0.5 0.5 40 42 44 2.4 0.66 ± 0.81Other 5 40 27.9 27.1 0.5 0.5 0.2 26 28 41 12.6 6.10 ± 1.84

Auckland 134 50 29.0 20.0 2.6 2.2 1.1 48 45 50 4.4 1.65 ± 0.26Dunedin 67 42 28.9 20.8 2.2 1.3 0.6 40 40 46 6.3 2.04 ± 0.55Yr2008 105 43 28.7 24.9 2.6 2.3 1.2 41 40 45 4.9 1.80 ± 0.42Yr2009 96 52 29.3 15.3 2.3 1.4 0.7 50 48 53 5.2 1.76 ± 0.28

Booth A 65 50 29.3 21.5 2.5 2.6 1.0 49 46 50 4.1 1.47 ± 0.33Booth B 69 51 28.8 18.7 2.7 1.8 1.3 47 45 49 4.6 1.82 ± 0.41Bed 1 33 42 29.2 24.3 3.1 1.6 0.6 45 46 53 6.8 2.35 ± 0.98Bed 2 34 42 28.7 17.5 1.3 1.0 0.6 35 34 40 5.9 1.75 ± 0.55

Booth A/European 17 52 26.4 45.7 4.1 3.9 1.3 64 63 65 2.5 0.96 ± 0.60Booth B/European 16 54 27.6 37.1 2.2 1.4 1.1 58 56 60 4.4 1.42 ± 0.71Bed 1/European 15 46 26.0 35.6 4.4 2.3 0.6 55 55 62 7.1 2.22 ± 1.46Bed 2/European 12 51 25.8 30.8 1.8 1.2 0.9 47 44 48 3.8 0.72 ± 0.71

†Here we define 1 SDD = 1 standard pre-vitamin D-weighted dose = 100 J m−2 ofvitamin D-weighted irradiance, analogous to the definition of 1 SED for standarderythemal dose. Note that this definition is not the same as that defined byWebb and Engelsen,31 where 1 SDD was taken as the optimum daily dose (i.e.,0.25 MED for 25% skin exposed for mid-latitude summer sun at noon), whichcorresponds to the UV equivalent of an oral dose of 1000 IU vitamin D.

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action spectrum. Further work is needed to resolve which actionspectrum is best, using a larger more homogenous populationsample, and with larger UV exposures. Greater attention shouldthus be paid to possible effects due to dietary differences.

It has been shown previously that baseline 25(OH)D3 mayaffect the sensitivity to changes in UV exposure.33,34 Further,as seen in Fig. 3, several participants with higher initial valuesshowed inconsistent results. As noted earlier, we investigatedthe effect of restricting the analysis to participants belowdifferent initial threshold serum 25(OH)D3 values, or to thosefor whom the interval between the solarium treatment and thefinal blood test fell into more restrictive ranges. Thesechanged the details, but did not significantly alter the overallpatterns shown in Fig. 7.

3.6. Results from using the statistical model

Up to this point, it has been assumed that population differ-ences between subsets are not important. Such differencescould however contribute to the observed difference betweensources since a different population subset was exposed toeach source. The uniformity in mean values shown in Table 1suggests it should not be an issue. However, we tested thatassumption with a statistical model.

The linear regression showed the artificial UV sourcesdiffered when controlling for the ambient UV exposure andmean 25(OH)D3 level (P = 0.007) but when the confoundingvariables associated with the participants (age, sex, BMI, ethni-city and skin reflectance) are added to the model the UVsource differences are reduced and not statistically significant(P = 0.47).

3.7. Implications for summer and winter vitamin Dproduction

Finally, we address the assertion that no vitamin D is producedin the mid latitude winter.35 It may be argued whether thevitamin D produced is actually zero, or merely whether it isbelow the detection threshold of measurements. Nevertheless,for a given dose of erythemally-weighted UV the production ofvitamin D must be smaller in winter compared with summer.For example, the calculated ratios of vitamin D productionbetween the summer and winter spectra are 10.8, 17.7, 38.1,and 42.7 for the CIE erythema, CIE Vitamin D, Olds VitaminD, and Bolsee Vitamin D action spectra, respectively. Since ittakes only a few minutes of daily exposure to maintain vitaminD levels in summer, the weightings with larger summer/winterratios (e.g., Olds and Bolsee) are more consistent with thefinding that it is difficult to maintain optimal vitamin D statusin the mid-latitude winter. Thus, on the basis of this infor-mation and the finding that results between sources are lessconsistent when using the currently accepted action spectrumfor vitamin D2 it appears that other possible action spectra forvitamin D production may be worthy of further consideration.

4. Conclusions

By making use of newly developed personal UV dosimeters, wewere able to assess the production of vitamin D due to rela-tively small exposures to UV radiation. The personal exposureto ambient UV outside the summer months is only a smallfraction of the available ambient UV dose, with mean exposure

Fig. 7 Mean increase in 25(OH)D3 per unit of UV exposure. The left panel is for erythemally-weighted UV, and the remainder are for three weightings for the pro-duction of pre-vitamin D in the skin. Points below the first dotted line represent changes for the subsets allocated to the 4 different artificial UV sources. Uncertaintyranges are standard errors of the mean. Note that the data point for Asian/Chinese has been clipped in the panel for the Bolsee weighting.

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fractions less than 3% for the Auckland participant, and lessthan 5% for the Dunedin participants. Further, approximately80% of the skin surface area was covered during daylighthours. Data from the period prior to the intervention from thecontrolled artificial UV source showed that the equivalent full-body exposures of doses from ambient UV are less than 0.5SED per week, which is insufficient to maintain current levelsof vitamin D in the population study group. This result is con-sistent with that from the full study, which have been reportedelsewhere.1

The intervention exposure of ∼2 SED to artificial UVsources reversed the mean seasonal decline in 25(OH)D3 andresulted in significant increases in 25(OH)D3. The productionof serum 25(OH)D3 per unit of equivalent full-body erythe-mally-weighted UV exposure was 1.78 ± 0.25 nmol per litre perSED. This sensitivity was similar at both sites, for both years ofthe study, and for both sexes. Results were also similar for allethnic groups considered, though there is a suggestion ofhigher sensitivities among Maori, and lower among Asians.That sensitivity is broadly consistent with the low dosethreshold used in our previous study, but is much greater thanthe sensitivity for large doses that were the focus of thatstudy.30

The main aim of the present study was to compare the pro-duction of serum 25(OH)D3 per unit of equivalent full-bodyweighted UV exposure between four different artificial UVsources to determine which of the four weighting functions(action spectra) considered gave the most consistent results.The mean sensitivity deduced for the currently accepted CIEaction spectrum for vitamin D production2 is 1.3 nmol perlitre per SDD (compared with 1.78 nmol per litre per SED forerythemally-weighted UV). Deduced sensitivities were muchgreater for the other two weightings. Unfortunately, measure-ment uncertainties were too large to be able to unequivocallyidentify which of the 4 action spectra gives the most consistentresults between the different UV sources; and none appearedto be any improvement over simply assuming that the actionspectra for erythema applies. However, any differences in sen-sitivities between sources were not statistically significant forany of the weighting function tested because the changes fromthe small UV doses were too small.

Although the artificial UV doses that were administered inthis intervention were relatively small, they are still large com-pared with the equivalent full-body exposures ambient UVreceived over the study period. The results of this interventionthus contributed significantly to the primary objective of thestudy, which was to determine the relationship between UVexposure and vitamin D status among the New Zealand popu-lation and its various subsets.

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