Jana Pavlíčková

Jiří Zbíral

Michaela Smatanová

Petr Habarta

Pavlína Houserová

Vlastimil Kubáň

Uptake of Thallium from Naturally Contaminated Soils into Vegetables 1 2 3

Keywords: Metals analysis -ICP, ICP/MS, Risk assessment Additives/Contaminants: Environmental contaminants, Toxic elements thallium, uptake, contamination, vegetables, kale, rape, kohlrabi, cucumber, 18 onion, parsley, celery, pot tests, pot trials 19 20 21

Thallium transfer from naturally (pedogeochemically) contaminated soils into vegetables 23 was studied. Three different types of top-soil (heavy medium and light) were used for pot 24 experiments. The soils were collected from areas with low, medium and high levels of 25 pedogeochemical thallium (0.3 1.5 and 3.3 mg kg -1 ). The samples of vegetables were 26 collected and analysed. The total content of thallium in soil and the type of soil (heavy, 27 medium, and light), plant species and plant variety were found to be the main factors 28 influencing thallium uptake by plants. The uptake of thallium from soils with naturally high 29 pedogeochemical content of this element can be high enough to seriously endanger food 30 chain. These findings are very important because of the high toxicity of thallium and the 31 absence of threshold limits for thallium in soils, agricultural products, feedstuffs and 32 foodstuffs in most countries, including the the Czech Republic

Thallium is a rare and dispersed element with a geochemical behaviour very near to K and 37 Rb [START_REF] Rehkämper | The mass balance of dissolved thallium in oceans[END_REF]. Thallium can mimic potassium in metabolic processes pedogeochemical content of this element. Higher transfer of thallium was observed in the 102 case of artificially contaminated soils. But the uptake of thallium from soils with naturally 103 high content of thallium was found to be high enough to seriously endanger food chain 104 [START_REF] Zbíral | Determination of Thallium in 373 Aqua-regia Soil Extracts by ICP-MS[END_REF][START_REF] Zbíral | Comparison of Several Soil Extractants for Determination of Thallium[END_REF][START_REF] Pavlíčková | Comparison of Aqua Regia and 329 HNO 3 +H 2 O 2 Procedures for Extraction of Twenty One Elements from Soils[END_REF][START_REF] Medek | Inductively Coupled 322 Plasma Mass Spectrometric Determination of Thallium in Soils and Winter Rapeseeds. 323 Intern[END_REF] No recommended maximum values are available at the present time in most countries. In 108 Germany 0.46 -2.24 mg kg -1 DM (or 0.4 -2 mg kg -1 88% DM) was established for feed 109 (anonymous 1997; ananymous 1998). We can take thallium concentration 0.4 -2 mg kg -1 110 DM for fodder crops and 0.25 -0.5 kg -1 DM for food as a provisional working limit. The 111 values 0.25 and 0.4 mg kg -1 DM were used for the evaluation of our results. Our study was 112 focused on two areas in the Czech Republic with naturally higher contents of thallium 113 found in our preliminary studies [START_REF] Sáňka | Evaluation of thallium content in arable spoil and 349 its influence on quality of agricultural production[END_REF][START_REF] Zbíral | Determination of Thallium in 373 Aqua-regia Soil Extracts by ICP-MS[END_REF][START_REF] Zbíral | Comparison of Several Soil Extractants for Determination of Thallium[END_REF] 114 [START_REF] Pavlíčková | Comparison of Aqua Regia and 329 HNO 3 +H 2 O 2 Procedures for Extraction of Twenty One Elements from Soils[END_REF][START_REF] Medek | Inductively Coupled 322 Plasma Mass Spectrometric Determination of Thallium in Soils and Winter Rapeseeds. 323 Intern[END_REF]Pavlíčková et al. 2005). The main goal was to 115 find suitable crops that can be planted in these areas without contamination of food chain 116 by thallium and also to find plants that should be avoided in the areas because of their 117 ability to accumulate thallium in their tissues. 171 Soil samples were air-dried gently crushed and sieved. Fraction < 2 mm according 172 to ISO 11464 was used for the analysis. Soils were digested [START_REF] Pavlíčková | Comparison of Aqua Regia and 329 HNO 3 +H 2 O 2 Procedures for Extraction of Twenty One Elements from Soils[END_REF] by 173 HNO 3 -H 2 O 2 (2 g soil sample 10 ml HNO 3 and20 ml H 2 O previous studies focused on this crop [START_REF] Zbíral | Determination of Thallium in 373 Aqua-regia Soil Extracts by ICP-MS[END_REF][START_REF] Zbíral | Comparison of Several Soil Extractants for Determination of Thallium[END_REF]Pavlíčková et 205 al. 2003;[START_REF] Medek | Inductively Coupled 322 Plasma Mass Spectrometric Determination of Thallium in Soils and Winter Rapeseeds. 323 Intern[END_REF]Pavlíčková et al. 2005). BAFs higher than 0.4 were found for 206 the other tested brassicaceous plants (except for stalk of kale and kohlrabi). BAF 2.6 was 207 observed as high as for the green part of kohlrabi.

209

The translocation factor -TLF (the ratio of thallium concentration in different parts of the 210 plant) shows that for most crops (brassicaceous and others) higher thallium concentration 211 is located in the green part of the plant. The highest TLF was found for kohlrabi (19), kale 212 (10), but also for onion (10) and carrot (8). Concentration of thallium in celeriac part of 213 celery was found to be higher than in the green part.

215

If we take thallium concentration 0.4 -2 mg kg -1 DM for fodder crops and 0.25 -0.5 kg -1

216

DM for food as a provisional working limit and adopt 0.25 and 0.4 mg kg -1 for the 217 evaluation (anonymous 1997; anonymous 1998) it can be concluded that for heavy soils 218 from Nivnice, and (a bit surprisingly) medium soils (Heřmanice) most crops and their parts 219 were below the limit. Straw of spring rape was above the limit and leaves of kale just on 220 the limit for food on medium soil (Heřmanice). The green part of kohlrabi was able to 221 accumulate thallium even from soil with only a background content of thallium and this part 222 of plant proved to be unsuitable for food or feed for all investigated soils. Brassicaceous that the ability of a plant to accumulate a metal compared to a control soil might not exist 237 for an anthropogenically contaminated soils and vice-versa. In addition thallium can be 238 present as Tl(I) or Tl(III) which makes it necessary to distinguish between these two 239 species (Lin et al. 1999a;Lin et al. 1999b). Without this specification a correct toxicological 240 evaluation is not possible particularly since Tl(I) possibly occurs in soluble whereas T(III) in 241 colloidal form.

  except rape seeds) were finely ground using a high-speed mill Grindomix 123 (Retsch, Germany) and digested by nitric acid in the closed high-pressure microwave 124 system (Ethos SEL, Milestone, Italy). Dry matter (DM) was determined (2 g of a sample 125 105 ºC) using a MA 30 moisture analyser (Sartorius GmbH, Goetingen, Germany). A 126 sixteen-position double heating block with digestion tubes and coolers MB 422 BH (Uni 127 Elektro, Hradec Králové, Czech Republic) was applied for soil digestion. A sub-boiling 128 distillation unit BSB-939-IR (Berghof BSB-939-IR, Germany) was used for purification of 129 nitric acid. ICP-MS ELAN 6000 (Perkin-Elmer SCIEX, Norwalk, USA) with a cross flow 130 nebulizer Scott's type spray chamber and Gilson 212 peristaltic pump was used for 131 determination of Tl. The MS part was regularly checked by a calibrating solution (Perkin-Pavlíčková et al. 2005). Operational parameters of the instruments are given in 135

159

  the harvest the plant parts were collected separately weighed and stored for analysis. 160 Sample preparation and digestion. 161 Plant samples were mechanically cleaned immediately after the harvest and subsequently 162 by a quick washing with deionised water to remove the rest of soil and dust particles. Plant 163 samples were dried and finely ground. The rapeseeds were analysed without grinding. The 164 all samples (1 g) were digested by nitric acid (8 ml HNO 3 and 10 ml H 2 O) in the microwave 165 digestion system at 145 ºC and 700 W for 5 min 180 ºC and 600 W for another 5 min and 166 finally at 180 ºC and 1000 W for the next 5 min. The digests were adjusted to the final 167 volume of 50 ml with deionized water. The digests were further diluted 1-20 times by 168 the ICP/MS measurement. Each series consisted of a suitable 169 amount of samples given by the procedure one internal reference standard and two 170 blanks.

  2 were used boiling for four hours 174 under cooler). Soil extracts were diluted 5 -10 times by deionized water before the 175 ICP/MS determination. Each series consisted of a suitable number of samples given by 176 the procedure two internal reference standards and two blanks.

177

  Determination of thallium by ICP/MS.178 Single element calibrating standard solutions were used for calibration of the ICP/MS 179 instrument at five different concentrations of thallium (0, 1, 5, 10 and 50 µg L -1 ). Lutetium 180 at the concentration 10 µg L -1 was used as an internal standard ( 175 Lu signals). The 181 extraction agents acids and lutetium concentrations in the standard calibrating solutions 182 matched their concentrations in the sample solutions. The calibration curve was linear in 183 the whole calibrating range (r  0.9999). Limit of detection 1.2 µg kg -1 was achieved for the 184 samples (3 S/N criterion). Thallium content was determined from 205 Tl signal. the pot experiments are given in Tables 4 and 5 for Brassicaceous plants 189 and the other crops respectively. The contents of thallium in different parts of the crops for 190 all three investigated soils are given in Figure 1. Average total uptake of thallium from the 191 experimental pot did not follow exactly the concentration of thallium in soil. Uptake of 192 thallium from the light soil (Lužice) with the highest content of thallium (3.3 mg kg -1 ) was 193 ten times higher than from both other soils. 194 195 The bioaccumulating factor -BAF (concentration of thallium in plant (or its 196 part)/concentration of thallium in soil) reflects thallium availability from the given soil. The 197 highest bioaccumulating factors were found for the light soil (Lužice) and than for the 198 heavy soil (Nivnice). Thallium in medium soil (Heřmanice) in spite of its relatively high level 199 (1.5 mg kg -1 ) was found to be less available. BAFs for non-brassicaceous plants were 200 usually below 0.1 even for the soil from Lužice. Higher BAFs for these plants were 201 observed for green parts of vegetables (onion, carrot, parsley) than for other parts. Celery 202 exception of this rule. The situation was substantially different for plants of 203 the Brassicaceae family. BAFs for spring and winter rape were near 1 as found also in the 204

  223plants grown on light soil (Lužice) substantially exceeded the limits with only one exception224-stalk of kale. Non-braccicaceous crops showed also relatively high concentration of 225 thallium on light soil (Lužice). The celeriac part of celery and the green part of parsley 226 exceeded the limit for food and the green parts of carrot and onion exceeded the limit for of thallium in soil, physico-chemical form and form of binding to soil 232 particles seem to be the main factors influencing the uptake by a plant. From the data 233 presented hereby it can be seen that thallium is an exception since the values obtained for

  by plants is species dependent. Plant varieties and plant parts differ in 244 the degree of uptake and accumulation of Tl. Some brassicaceous plants commonly grown 245 as vegetables behave as hyperaccumulators of Tl. Content of thallium in different aerial 246 parts of tested plants can differ substantially (nearly 20 times in maximum). The highest 247 concentration was observed mainly in the green parts of the particular plants. Green part 248 of kohlrabi can contain thallium in concentration exceeding the provisional limit even if 249 grown on soil with very low natural content of Tl. 250 251 The concentration of thallium in vegetables in many cases can substantially exceed the 252 concentration of thallium in soils. Thus thallium content should be monitored and the plants 253 with high thallium accumulation power should be excluded from growing for human or 254 animal nutrition in contaminated areas. The above mentioned facts are often neglected 255 because legal measures are usually taken only for the areas anthropogenically 256 contaminated as a result of a human activity. Uptake of thallium from soils with naturally 257 high content of thallium can be high enough to seriously endanger food chains (directly by 258 consumption of plants grown on contaminated soils indirectly by consumption of meat from 259 animals feed by rape cattle cakes a by-product of rapeseed oil production).

379 Fig. 1 .

 3791 Fig.1. Relationship between content of thallium [in mg kg -1 DM] in the soil and its uptake

  between the content of thallium [in mg kg -1 DM] in the soil and its uptake by separate parts of test 425 plants [in mg kg -1 DM] for Brassicaceous plants (bottom) and the other crops (top) respectively

  ; Pavlíčková

	105
	106	et al. 2005).
	107

Table 1 .

 1 All reagents and standard solutions were prepared using Milli Q deionised water (Millipore,

	138
	139	Bedford, USA). All chemicals were of reagent grade purity purchased from (Analytika,
	140	Prague, Czech Republic) and Merck (Darmstadt, Germany). Stock standard solutions
	141	1000 ± 2 mg L -1 Tl in 2% (v/v) nitric acid and 1000 ± 2 mg L -1 Lu in 2% (v/v) nitric acid
	142	(Analytika, Prague, Czech Republic) were used for preparing of calibrating standard
	143	solutions.
	144	Pot experiments
	145	Soils with different pedogeochemical contents of Tl. Three different soils were collected -
	146	Nivnice (heavy soil -HS 0.3 mg Tl kg -1 DM), Heřmanice (medium soil -MS 1.5 mg Tl kg -1
	147	DM) and Lužice (light soil -LS 3.3 mg Tl kg -1 DM). The content of thallium (expressed as
	148	mg Tl kg -1 of dry matter -DM) in all cases was only of pedogeochemical origin. Basic
	149	characteristics of the soils are summarised in Table 2. 7.5 kg of air-dried soil (particles less
	150	than 2 cm) were used for filling a pot. Six replicates for each soil and each plant (90 pots
	151	for the experiment) were used. Five crops -spring rape, winter rape, kale, kohlrabi and
	152	maize were tested in the first year and celery, parsley, carrot, and onion were tested in the
	153	same pots next year (for the scheme of the experiment see Table 3). Winter rape was
	154	sowed in each pot in August. Normally developed plants were singled out in September.
	155	Other crops were sowed in April and singled out in May. The fully matured plants were
	156	harvested in July. The soils were fertilized with N (NH 4 NO 3 ), P (CaHPO 4 .2 H 2 O) and K
		(KCl)

136

Reagents.

137

according to the individual demands of each crop to provide a sufficient nutrient 157 supply. The pots were protected against rain during the whole period. Soil moisture was

	158
	adjusted to 60% of maximum water capacity by daily watering with deionized water. During

Table 2 .

 2 Basic Characteristics of Topsoils a Used for Pot Experiments (All Data Given for DM)

	382
	383
	384
	385

a Nivnice (heavy soil) Heřmanice (medium soil) and Lužice (light soil). 392 b Content in H 2 O 2 -HNO 3 extract. c Content according to Mehlich 3. d oxidized forms of carbon. e

Table 3 .

 3 Species and Cultivars Used in Experiments

	395
	396
		Plant 1	Species	Cultivar 2	Pot 3	Symbol 4
		Maize 5	Zea mays L.	Cemilk H285	12/4	A
		Celery 6	Apium graveolens var. Rapaceum	Maxim	-/2	A
		Parsley 6	Petroselinum crispum cvar. Erfurtense	Dobra	20/8	B
		Carrot 6	Daucus carota L.	Berjo	20/8	C
		Onion 7	Allium cepa L.	Všetana	-/6	D
		Spring rape 8 Brassica napus L. cvar. Napus 9	Golda	20/10	E
		Winter rape 8 Brassica napus L. cvar. Napus	Zoro	20/10	D
		Kale 8	Brassica oleracea L. var. Acephala	Winterbor F1	6/2	B
		Kohlrabi 8	Brassica oleraceae L. cvar. Gongylodes	Olmia	6/2	C
	397
	398	1 family 2 cultivar/trade name 3 number of seeds/plants per pot 4 sequence of the tests in 2002/2003
	399	years A/A B/B C/C and D/D 5 Maize 6 Apiaceae 7 Liliaceae 8 Brassicaceae 9 form annua
	400
	401

Table 4 .

 4 Non-Brassicaceous Plants. Average Yield of Vegetables (Plants) [g DM] Average Total 402 Uptake of thallium [µg] by Vegetables from One Pot The Biological Absorption Coefficients (BAC

	403
	404	= plant/soil concentration quotient) The Translocation Factor (TLF = Leaves (Straw)/Root (Stalk
	405	Seeds) thallium Concentration).
	406
			Maize	Celery	Parsley		Carrot	Onion
		Site b	Leaves	Root	Leaves	Root	Leaves	Root	Leaves	Onion	Tops
				(celeriac)	(tops)
					Average Yield in One Pot [g DM]
		Nivnice	75.6 (3)	34.8 (12) 26.5 (16) 27.5 (16) 21.8 (10) 27.7 (24) 17.0 (19) 12.7 (26) 2.9 (19)
		Heřmanice 63.8 (8)	18.2 (27) 13.8 (16) 22.7 (14) 16.3 (6)	15.3 (15) 8.9 (16)	8.0 (14)	2.3 (12)
		Lužice	65.6 (9)	3.8 (42)	4.7 (27)	3.4 (33)	3.8 (28)	5.6 (64)	5.4 (35)	7.0 (24)	1.6 (25)
				Average Total Uptake of Thallium from One Pot [µg]
		Nivnice	0.13 (3)	0.37 (20) 0.19 (18) 0.12 (12) 0.14 (28) 0.09 (15) 0.40 (30) 0.02 (21) 0.05 (19)
		Heřmanice 0.20 (22) 0.79 (25) 0.24 (31) 0.40 (19) 0.53 (24) 0.18 (19) 0.86 (32) 0.05 (17) 0.09 (15)
		Lužice	1.99 (7)	1.21 (41) 0.78 (20) 0.67 (36) 1.41 (37) 1.02 (38) 2.84 (25) 0.91 (32) 1.33 (33)
						Average BAC
		Nivnice	0.006 (0.3) 0.036 (22) 0.024 (20) 0.015 (16) 0.021 (20) 0.011 (18) 0.079 (32) 0.006 (22) 0.057 (24)
		Heřmanice 0.002 (21) 0.029 (14) 0.011 (22) 0.012 (11) 0.022 (23) 0.008 (16) 0.066 (35) 0.004 (6) 0.027 (11)
		Lužice	0.008 (8) 0.098 (17) 0.051 (16) 0.061 (23) 0.111 (22) 0.071 (14) 0.165 (15) 0.040 (16) 0.243 (14)
						Average TLF
		Nivnice	_	0.7 (34)	1.5 (29)	7.1 (36)	10.1 (15)
		Heřmanice	_	0.8 (34)	1.8 (19)	8.3 (31)	6.5 (16)
		Lužice	_	0.4 (31)	1.8 (21)	2.3 (16)	6.2 (11)
	407
	409
	410
	411

a RSD [%] is given in parenthesis (n = 6). b Nivnice (heavy soil) Heřmanice (medium soil) and 408 Lužice (light soil).

Table 5 .

 5 Brassicaceous Plants. Average Yield of Vegetables (Plants) [g DM], Average Total Uptake 412 of Thallium [µg] by Vegetables from One Pot, the Biological Absorption Coefficients (BAC = RSD [%] is given in parenthesis (n = 6). b Nivnice (heavy soil) Heřmanice (medium soil) and Lužice (light soil). 416

	413
	414	plant/soil concentration quotient), and the Translocation Factor (TLF = Leaves (Straw)/Root (Stalk
	415	Seeds) Thallium Concentration).
				kale	spring rape	winter rape (17)	kohlrabi
		site b	stalk	leaves	seeds	straw	seeds	straw	root	leaves
					Average Yield in One Pot [g DM]
		Nivnice	3.3 (21)	14.7 (28)	10.7 (18)	34.7 (11)	7.4 (26)	15.4 (26)	9.4 (49)	20.1 (15)
		Heřmanice 1.9 (9)	8.2 (14)	no seed	24.7 (14)	5.7 (23)	13.4 (22)	7.3 (13)	10.9 (16)
		Lužice	2.4 (20)	11.7 (7)	2.2 (46)	30.0 (9)	4.2 (16)	14.2 (18)	7.0 (20)	11.8 (6)
				Average Total Uptake of Thallium from One Pot [µg]
		Nivnice	0.06(32)	2.23 (26)	1.64 (18)	3.13 (9)	1.21 (37)	2.27 (22)	0.32 (36)	12.0 (17)
		Heřmanice 0.05 (16)	2.04 (14)	no seed	9.58 (22)	1.13 (26)	2.45 (15)	0.45 (23)	12.2 (23)
		Lužice	0.36 (23)	18.1 (7)	5.50 (35)	42.6 (16)	14.7 (29)	36.1 (18)	4.46 (38)	96.4 (31)
						Average BAC
		Nivnice	0.065 (13) 0.515 (13) 0.511 (5)	0.303 (11) 0.539 (23) 0.500 (13) 0.096 (18) 1.94 (8)
		Heřmanice 0.017 (18) 0.166 (6)	no seed	0.261 (9)	0.132 (19) 0.124 (13) 0.043 (26) 0.70 (14)
		Lužice	0.046 (12) 0.470 (2)	0.804 (21) 0.432 (17) 1.07 (24)	0.743 (24) 0.192 (29) 2.60 (20)
						Average TLF
		Nivnice		8 (14)	0.6 (12)		1 (21)	19 (17)
		Heřmanice	10 (17)	No seed		1 (20)	17 (16)
		Lužice	10 (12)	0.5 (11)	0.7 (12)	14 (14)

a

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants

Acknowledgments

support from the Grant Agency of the Czech Republic, grant No. GA ČR 264 525/01/0908, and from the Ministry of Education Youth and Sports of the Czech Republic, 265 grant No. MSM 43210001 is gratefully acknowledged.


Nektaria Polychronaki

Paul C Turner

Hannu Mykkanen

Yunyun Gong

Hassan Amra

Mosaad Attia

Hani El-Nezami

Polychronaki Nektaria

Turner C Paul

Mykkänen Hannu

Amra Hassan

Abdel-Wahhab Mosaad

El-Nezami Hani

Determinants of AFM1 in breast milk in a selected group of Egyptian mothers

Keywords: Chromatography -HPLC, Statistical analysis, Extraction Egypt, breast milk, aflatoxin M 1, exposure, infants 16

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction 1

Breast milk is considered to be the ideal food for the infant [START_REF] Pronczuk | Breast milk: an optimal food[END_REF]WHO 2003), 2 and the importance of breast-feeding for normal growth and development has become 3 increasingly recognized. However, in addition to its nutritionally and immunologically 4 beneficial components, human milk may contain trace amounts of a wide range of contaminants 5 following maternal dietary exposures [START_REF] Jensen | Chemical contaminants into human milk[END_REF]. In some less developed parts 6 of the world a family of highly toxic and carcinogenic naturally occurring compounds, nurse and thirty minutes were needed for completion. The FFQ focused on foods more likely to 1 contribute to dietary intake of aflatoxins and consisted of two components: a food list and a 2 frequency response section. The data on food use were expressed as frequencies ranging from 3 several times a day to never. The groups of food included grain products (wheat bread, corn 4 bread, pasta, rice, corn), milk and milk products (Romano cheese, feta cheese, cream), legumes 5 (beans, lentils), meat (chicken, beef, lamb), fish, corn oil, cottonseed oil, dried fruits, and 6 peanuts. These food groups include those likely to be aflatoxin contamination in Egypt (El-

3

Extraction of aflatoxins from milk samples was modified from the method of El-Nezami et al 4 (1995). Briefly, 10 ml breast milk samples were warmed to 37 o C and were shaken to distribute 5 fat. For defatting, the samples were centrifuged (3000g, 15 min, 5 o C) and filtered via glass 6 wool. To facilitate the passage through a C18 cartridge (Strata C18-E, 50 um, 70A, 7 Phenomenex, USA), the samples were diluted 1:1 with milli-Q water. The cartridge was pre-8 activated with 10 ml acetonitrile and then 10 ml of water, prior to passage of diluted breast milk 9 at a flow rate of 3.5 ml/ min. The loaded cartridge was then washed with 10 ml water, 10 ml 10 basic acetonitrile/ water (1% ammonia, 10% acetonitrile) and 10 ml acidic acetonitrile/water 11 (1% acetic acid, 10% acetonitrile). AFM 1 was eluted with 5 ml acidic acetonitrile (1% acetic 12 acid, 40% acetonitrile). AFM 1 was extracted twice from the eluent with 2 ml dichloromethane.

13

Following centrifugation (3000g, 15 min) to separate the layers, the two dichloromethane 14 fractions were pooled and dried under nitrogen gas. The residue was dissolved in 0.7 ml of 15 methanol.

16

HPLC analysis

17

Reverse phase HPLC (model LC-10ADvp solvent delivery system; model SIL-10Advp auto 18 injector, Shimadzu, Japan; ODS-5 C18 Brownlee reverse phase column (220 x 4.6 mm, particle 19 size 5 µm) with a C18 guard column (Perkin Elmer, Norwalk, Conn.) was used to determine the 20 level of AFM 1 in breast milk extracts. An isocratic system with water: methanol: acetonitrile 21 66:17:17, flow rate 1 ml/ min, oven temperature 40 o C and injection volume of 30 µl were used.

22

Detection was by excitation at 360 nm and emission at 440 nm (Fluorescence-10A XL, 23 Shimadzu detector) (Figure 1). The concentrations of AFM 1 in milk were estimated from a 24 standard curve 0.04-10 ng/ ml methanol, prepared from AFM 1 in chloroform (9.93 ug/ ml) 25 reference material RM 423 (LGC Promochem AB, Borås, Sweden). An AFM 1 standard was 26 injected every 10 injections as a quality control, AFM 1 was stored at -20 o C in a sylilated vial 27 wrapped in aluminium foil. Since AFM 1 is a possible carcinogen, care was exercised to avoid University Hospital (Kuopio, Finland). These breast milk samples were extracted and analyzed 9 by the method described above. AFM 1 was not detected in these samples. For the recovery 10 studies seven aflatoxin non detect breast milk samples (triplicates) were spiked with 12.5, 25, 11 50, 125, 250, 375, 500 pg AFM 1 / ml milk. One water sample (triplicates) was spiked with 250 12 pg AFM 1 / ml water. AFM 1 was extracted from the samples as previously described. The 13 average percentages of aflatoxin recovered were 88 ±28 and 94 ±8 from breast milk and milli-Q 14 water respectively. Correlation coefficient between AFM 1 added and AFM 1 recovered from 15 spiked breast milk was 0.993. The identity of AFM 1 was confirmed through spiking of positive 16 breast milk samples with AFM 1 , and by derivatization of AFM 1 to form AFM 2a according to the 17 method of AOAC international (AOAC 1995).

19

To assess the repeatability of the method, breast milk samples were spiked with 250 pg AFM 1 / 20 ml milk (4 replicates). The analysis gave a mean value of 205 ±15 pg/ ml milk and 8% 21 coefficient of variation.

23

The limit of detection was 0.06 ng AFM 1 /ml methanol or 4.2 pg AFM 1 / ml of breast milk based 24 on a 10-ml breast milk sample and reconstitution of extracts with 0.7 ml of methanol, and was 25 defined as the lowest concentration of AFM 1 that could be reliably detected (>3:1 signal to 26 noise ratio) and quantified (% CV <20) for triplicate extractions. presence/absence of AFM 1 in their breast milk, and chi-square test was used to associate the 12 presence of AFM 1 in breast milk with categorical variables. Logistic regression models were 13 used to analyse the association of each potential factor and AFM1 presence/ absence. For the 14 FFQ data analysis, the food-consumption data were either regrouped into the two categories of 15 "daily consumption" and "weekly or monthly consumption" (the category "never" was included 16 to the "weekly or monthly consumption" category); or treated as continuous variable, i.e. the 17 reported frequencies of consumption were expressed as a number representing the frequency of 18 consumption. eg. 1/ month, 1/ fortnight, 1/ week or 3-4 times/ week equal 1/ 30 or 0.03, 1/ 15 or 19 0.06, 1/ 7 or 0.21, 3.5/ 7 or 0.5 respectively (Willet 1990). Missing data points in the results 20 presented reflect individuals for whom in one or more variable was missing for that analysis 21 being reported.

23

Results

24

Descriptive characteristics and food consumption data 25 Descriptive data of 388 mothers and their infants are presented in Tables 1 and2 category and 89% of the mothers were not employed and were either at home or involved in 1 farming. Corn bread, wheat bread, corn oil, cotton seed oil and beans were used in a daily basis 2 by most of the mothers, but mothers belonging to the LSES category more frequently consumed 3 beans (p= 0.009), corn oil (p= 0.001), and cotton seed oil (p= 0.001) than mothers belonging to 4 the HSES category. Fifteen percent of the mothers were obese (BMI>30), and obese mothers 5 were consumers of corn oil more frequently than the non obese mothers (84 vs 67%, p= 0.020).

6

A few of mothers (6.2%) reported a health problem associated with liver or intestine function, 7 while two percent of the mothers reported intake of medicines such as blood pressure reducing 8 tablets and anti-depressant tablets, or dietary supplements such as iron and calcium tablets. 9 10 [Insert Tables 1 and2 about here] 11 12 There were 227 boys and 159 girls in the study (mean age 5.9 months: range 0.2-33 months). 13 There were no reported illnesses within any of the infants. Anthropometric measures revealed 14 the prevalence rate for stunting (HAZ≤-2) was 35.7%, for being underweight (WAZ≤-2) 14.4%, 15 and for wasting (WHZ≤-2) 0.6%. A total of 78 (23.4%) children had a z score of ≤ -3 in at least 16 one parameter (extreme malnutrition). Median z-scores (IQR) for the infants were below zero 17 for stunting and being underweight, but not for wasting (-1.49 (-2.63-0.02), -0.45 (-1.47-0.43) 18 and 0.82 (0.17-1.66) respectively).When divided into quartiles by age a significant inverse 19 trend was observed with age for both stunting (p= 0.001) and being underweight (p= 0.004) 20 (Table 3). For both stunting and being underweight infants <2 months had the highest median Z-21 scores (-0.73 (-1.98-0.14) and -0.29 (-1. 16 occurring at moderate levels compared to some of the higher risk regions of Africa and south 2 east Asia. It is difficult to determine the average daily aflatoxin intake of the infant based on 3 breast milk exposure. Firstly, the maternal intake of aflatoxins will vary from day to day, and 4 thus breast milk levels will fluctuate. Aflatoxin or its metabolites may also be stored in fat 5 reserves though the levels and contribution, if any, to breast milk levels at a given stage of 6 lactation are not known. Secondly, the fat content and total milk volume will vary within a feed 7 and between feeds, and this will likely impact on the levels of aflatoxins observed. Thirdly, the 8 average volume an infant will consume in a day will vary. Despite these difficulties we can 9 make some estimates of aflatoxin intake in the 138 mothers with detectable AFM 1 in breast 10 milk. Assuming average daily milk volume 500 ml, the average intake of AFM 1 by the infant 11 can be estimated to be 6.75 ng/ day. Assuming AFM 1 in human milk represents 0.09% to 0.43% 12 of dietary intake (Zarba et al. 1992), maternal intake is estimated at 1570 to 7500 ng/ day. The 13 calculated average daily intake by all women in two high risk regions for aflatoxin exposure

2

In Egypt, weaning foods are those consumed by the rest of the household, and the fact that 3 mothers are exposed ensures the exposure of their children. Overall the breast milk 4 contamination with aflatoxin is moderate, compared to some high exposure regions. However, 5 for genotoxic carcinogenic substances such as aflatoxins, a threshold value below which the risk 6 value for human health is equal to zero does not exist. The Joint FAO/WHO Expert Committee 7 on Food Additives (JEFCA) does not establish a tolerable daily intake (TDI), but strongly 8 recommends that the level of aflatoxin should be as low as possible. Therefore, the toxicological 9 significance of the presence of aflatoxin in maternal milk should not be overlooked.

  7 aflatoxins (AFs), have been observed in breast milk (Abdulrazzaq et al. 2003; El-Nezami et al. 8 1995; IARC 1993; Navas et al. 2005; Zarba et al. 1992). Aflatoxin B 1 (AFB 1 ), a potent liver 9 carcinogen, is the most commonly occurring and carcinogenic of the aflatoxins, and is classified 10 as a class 1A human carcinogen (IARC 1993). Maternal consumption of aflatoxin contaminated 11 food whilst breast feeding can result in the accumulation of aflatoxins and their metabolites in 12 breast milk. Approximately 95% of AFB 1 metabolites excreted in milk are in the form of AFM 1 , 13 though AFM 2 , AFG 1 and AFB 1 are also reported (Abdulrazzaq et al. 2003; El-Nezami et al. 14 1995; Turconi et al. 2004; Zarba et al. 1992). IARC (1993) has classified AFM 1 as a proven 15 animal carcinogen, but as yet there is insufficient data to be classified a human carcinogen, and 16 thus is regarded as a possible human carcinogen (group 2B). In addition to being potent 17 carcinogens, aflatoxins may contribute to early childhood growth faltering (Turner et al. 2003), 18 and particularly strong associations have been reported around the weaning stage in Beninese 19 infants (Gong et al. 2002, 2004). In addition a reduced level of salivary sIgA has been 20 associated with aflatoxin exposure in Gambian children (Turner et al. 2003). More recently the 21 immune status of Ghanaian adults has been reportedly affected by aflatoxin exposure (are at high risk for aflatoxin contamination it is important to understand exposure 25 patterns using aflatoxin biomarkers during pregnancy and early infancy to assess the health 26 consequence to the child. Exposure during pregnancy leads to in utero exposures (Wild et al.

  27 1991), and then during early breast feeding AFM 1 is likely to be the major aflatoxin ingested by 28

7

  Nezami et al. 2000; Hifnawy et al. 2004; Selim et al. 1996). Complete dietary data was received 8 from all study subjects. 9 10 Socioeconomic data (working status, income, level of education), demographical data (place of 11 residence, age), and clinical data (health status, miscarriages, medication) were recorded by 12 interview while the anthropometrical data (mother's weight and height, baby's weight and 13 height current and at delivery) were taken from the reports of the New El-Qalyub Hospital 14 where the mothers were followed since the delivery. Child body weight was measured by 15 nursing staff using a Tanita 1584, Precision weighing Balance, Bradford, MA (max weight 20 16 kg, accuracy 50 g). The socioeconomic status of the households was dichotomized in categories 17 of either higher or lower (HSES/ LSES). HSES included families with one or both parents 18 working and at least one work demanding higher education (teachers, nurses, government 19 employees, police officers etc.), and LSES one or none of parents working and the work not 20 demanding higher education (butcher, carpenter, tailor, salesman, conductor, driver, farmer 21 etc.), respectively. For assessing children's growth status, the measured anthropometric values 22 (baby's weight and height) were expressed as standard deviations (Z-scores) below or above the 23 median value of the international reference population recommended by the National Centre of 24 Health Statistics/World Health Organization (WHO) (WHO 1995). Weight for height Z-score 25 (WHZ), weight for age Z-score (WAZ), and height for age Z-score (HAZ) below -2 reflects 26 malnutrition, while a value below -3 severe malnutrition. collected into a sterile plastic container by self-expression prior nursing the 2 baby. The sample was kept at 4 o C and frozen within one day at -20 o C prior to extraction.

  proper decontamination procedures with 10 % sodium hypochlorite were 1 used. HPLC grade methanol, acetonitrile and dichloromethane were purchased from 2 Sigma/Aldrich Chemical Co. (Kemia Oy, Helsinki, Finland).

  of the measurement of breast milk aflatoxin was carried out using 7 breast milk samples of Finnish mothers kindly provided by the Breast Milk Centre of Kuopio 8

  approved by the Ethics Committee of the University of Kuopio and Kuopio 2 University Hospital in Finland and by the National Research Centre Ethical Committee in 3 Egypt. All subjects were made aware of the content of the study and if they agreed to 4 participate, a written informed consent was obtained. 5 Statistical analysis 6 SPSS 11.0 for windows was used in the statistical analysis of the data. AFM 1 values did not 7 follow normal distribution even after logarithmic transformation (p= 0.005, Kolmogorov-8 Smirnov normality test). Therefore, to identify possible associations between AFM 1 levels and 9 related factors, the non-parametric Mann-Whitney U (or Kruskal-Wallis) test or Spearman 10 correlation were used for continues variables. The mothers were dichotomized depending on the 11

  . The median 26 age of the mothers was 25 years (range 15-47), most mothers (71.6%) already had one or more

(

  14consumption were collinear to each other which restricted from being present in the same 15 model. Therefore, separate models including either of these two factors were generated. When 16 BMI was taken into consideration, mum's age, non working status, having more than one child, 17 early lactation stage (<1 month), and obesity appeared to be strong predictors of the AFM 1 18 presence; non working mothers were 2.87 times more probable to be AFM 1 positive than the 19 working ones (p= 0.018), having more than one child almost doubled the risk of being AFM 1 20 positive (p= 0.025) and early lactation stage (<1 month) seemed to be a strong predictor of the 21 presence of AFM 1 with an OR of 3.57 (p= 0.028). BMI had a significant overall effect to the 22 AFM 1 presence (p= 0.011). There was no difference in AFM 1 frequency for overweight mothers 23 (BMI 25-30) compared to those with BMI ≤25 (p= 0.57), though obese mothers (BMI ≥30) had 24 three times greater risk of being positive to AFM 1 than those with BMI ≤25 (p= 0.004). In the 25 multivariate corn oil consumption model (excluding BMI), mothers with daily corn oil 26 consumption had 2.21 times greater risk of being AFM 1 positive than the non frequent 27 0.002). Replacing BMI with corn oil in the model didn't alter significantly the 1 strengths of the associations between the other variables and AFM 1 presence.2Consumption of other grain products, milk and milk products, meat, fish, legumes, cotton seed 3 oil, dried fruits and peanuts did not show any significant associations with AFM 1 in breast milk 4 highly susceptible population group for exposure to environmental toxicants for a 10 variety of reasons, including lower detoxification capacity, rapid growth, higher intakes of air, 11 food and water per kg body weight (Weaver et al. 1998) and therefore, early childhood exposure 12 to the carcinogenic aflatoxins may be critical determinants of later health effects. Exposures in 13 utero and through early infancy may additionally be important. AFM 1 in breast milk is a marker 14 of dietary exposure of the mother to AFB 1 and consequently aflatoxin exposure to the breast-15 feeding infant(Zarba et al. 1992). In this study 35.5% of mothers were positive for breast milk 16 AFM 1 . The frequency is higher than that previously reported for this region (El-Shewy 1987), 17 though this may reflect advances in analytical sensitivity. In our study the median level was 18 13.5 pg/ ml, range 5-5000pg/ ml compared to that of El-Shewy et al(1987) who reported 22/ 19 200 (11%) of samples were positive with a mean of those positive of 160 pg/ ml, range 120-200 20 pg/ ml. The AFM 1 levels in the breast milk of the Egyptian mothers are lower than the levels 21 reported elsewhere. AFM 1 was observed in breast milk from 129/ 140 (92%) of samples in the 22 United Arab Emirates with median level for positives of 560 pg/ ml (range 5-3400 pg/ ml) 23 (Abdulrazzaq et al. 2003). El Nezami et al (El-Nezami et al. 1995) reported the median breast 24 milk AFM 1 levels in 11/ 73 (15%) to be 71 pg/ ml (range 28-1031pg/ ml) in Victoria, Australia 25 and 5/ 11 (45%) to be 664 pg/ ml (range 39-1736 pg/ml) in Thailand. In the Gambia, West 26 Africa all five breast milk samples analysed were positive for AFM 1 with total milk values of 27 2100-9200 pg reported (Zarba et al. 1992).

14 were 8 FoodFood

 8 µg AFB 1 in Zhuqing, China (Wang et al. 2001)and 15.7 µg total aflatoxins in The 15 Gambia, West Africa (Groopman et al. 1992). Given that about 65% of mothers in our study 16 were not included in this estimate, the overall levels of these Egyptian mothers is modest by 17 comparison. Wean foods are introduced from about 4-6 months which are likely to also be 18 contaminated if parental food is contaminated, thus the overall contribution to aflatoxin 19 exposure from breast milk will decline with time. However, breast feeding in Egypt, like other 20 African countries, often continues until infants are two years old, and thus over this extended 21 period the contribution made by breast milk may be important. 22 23 In Egypt the sources of aflatoxin exposure are less well defined than those of West Africa 24 (Turner et al., 2005). Non-working status, high BMI and/or corn oil consumption, number of 25 children (>1), and early lactation stage contributed to the occurrence of aflatoxin in breast milk 26 reported in this study. The non-working mothers were not employed but mostly belonged in 27 small farmer communities, they were involved with farming and family work. In small farmer 28 Page 12 of 25 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk crops after being harvested are left to dry over plastic or synthetic sheets, 1 which may promote Aspergillus growth and toxin production (Turner et al. 2005). Most of these 2 crops are consumed locally by either the household or closer communities. High BMI seemed to 3 act as an indicator of the amount and type of food consumed including corn oil, with obese 4 mothers consuming corn oil more frequently than the non-obese mothers. Worldwide two of the 5 major sources of aflatoxin exposure are groundnuts and corn, thus corn oil is a potential source 6 of aflatoxin exposure in this region (El-Sayed et al. 2003; El-Tahan et al. 2000; Hifnawy et al.72004). The fact that obese mothers had higher AFM 1 levels than the non-obese, possibly reflects 8 the frequency of consumption of corn oil, and thus weakened contribution of corn oil to breast 9 milk AFM 1 level in our analysis when both factors were considered.10 11The observed frequency of AFM 1 positivity and child number was not expected, though a higher 12 number of children may act as indicator of lower socioeconomic status and therefore restricted 13 diet. However, in our analysis did not reveal an association between socioeconomic status and 14 AFM 1 positivity. The mothers at early lactation stage (<1 month) had given birth no more than 15 15 days before the breast milk sample was taken. The relative proportions of milk components 16 vary significantly with the stage of lactation, especially in the beginning of lactation (Lawrence 17 1999), and it is possible that changes in total fat content are important in terms of accumulation 18 and mobilization of aflatoxins. 19 20 In developing countries growth faltering is often associated with the quantity and/ or poor 21 quality of foods, in addition to multiple infectious hazards (WHO 2003). However, high levels 22 of aflatoxin-albumin adducts have been associated with growth faltering in Beninese infants 23 (Gong et al., 2002; 2004). In common with many developing countries (Shrimpton et al. 2001) 24 Egyptian infants had a high prevalence of stunting and a moderate frequency of being 25 underweight, based on WHO criteria (WHO 1995). In this study we do not have biomarkers of 26 infant aflatoxin exposure, though the modest maternal breast milk levels of AFM1 would 27 predict overall exposures from milk or weaning foods to be considerably lower than in the 28 Page 13 of 25 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk may be more informative in this respect.

Food[

  10 Consequently, a reduction of mother's exposure to aflatoxins and thus, a reduction of children's 11 exposure through the breast milk is desirable. Reductions in aflatoxin exposure can be 12 envisaged by several approaches. Where the source of contamination is clearly defined such as 13 in Guinea, West Africa, post harvest changes to drying and storage of at risk foods is effective 14 (Turner et al. 2005). Where dietary sources are less well defined such as in Egypt, reduction in 15 uptake of aflatoxins may be achieved by dietary modulation, eg. with chlorophyllin (Egner et al. 16 2001) or probiotics (El-Nezami et al. in press).17Page 14 of 25 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk Osman N, Yousif ZM, Al-Falahi S. 2003. Aflatoxin M1 in breast-milk of 5 UAE women. Ann Trop Paediatr. 23: 173-179. 6 7 Angelico M and Renganathan E and Gandin C and Fathy M and Profili MC and Refai W et al. 8 1997. Chronic liver disease in the Alexandria governorate, Egypt: contribution of 9 schistosomiasis and hepatitis virus infections. J Hepatol. 26: 236-243. 10 11 AOAC. 1995. Aflatoxins M1 and M2 in fluid milk (Scott PM, ed) In: Natural Toxins. Arlington, 12 VA: Association of Official Analytical Chemists. 49: 34-35. 13 14 Egner PA, Wang JB, Zhu YR, Zhang BC, Wu Y, Zhang QN et al. 2001. Chlorophyllin 15 intervention reduces aflatoxin-DNA adducts in individuals at high risk for liver cancer. Proc 16 Natl Acad Sci U S A. 98: 14601-14606. 17 18 El-Nezami H, Ma J, Polychronaki N, Zhu H, Ling W, Salminen EK et al.. Probiotic 19 supplementation reduced biomarker for increased risk of liver cancer in young Chinese males 20 from Southern China. Amr J. Clin Nutri. In press. 21 22 El-Nezami H, Mykkänen H, Kankaanpaa P, Suomalainen T, Salminen S, Ahokas J. 2000. 23 Ability of a mixture of lactobacillus and propionibacterium to influence the faecal aflatoxin 24 content in healthy Egyptian volunteers: a pilot clinical study. Bioscience Microflora. 19: 41-45. 25 26 El-Nezami H, Nicoletti G, Neal GE, Donohue DC, Ahokas JT. 1995. Aflatoxin M1 in human 27 breast milk samples from Victoria, Australia and Thailand. Food Chem Toxicol. 33: 173-179. AM, Soher EA, Sahab AF. 2003. Occurrence of certain mycotoxins in corn and corn-2 based products and thermostability of fumonisin B1 during processing. Nahrung. 47: 222-225. 3 4 El-Shewy EA. 1987. Some Toxicological Studies on contaminated breast milk by aflatoxins 5 PhD thesis]. Egypt, Faculty of Medicine: Zagazig University, Benha Branch 6 7 El-Tahan FH, El-Tahan MH, Shebl MA. 2000. Occurrence of aflatoxins in cereal grains from 8 four Egyptian governorates. Nahrung. 44: 279-280. 9 10 Gong Y and Cardwell K and Hounsa A and Egal S and Turner PC and Hall AJ et al. 2002. 11 Dietary aflatoxin exposure and impaired growth in young children from Benin and Togo: cross 12 sectional study. BMJ. 325: 20-21. 13 14 Gong Y and Hounsa A and Egal S and Turner PC and Sutcliffe AE and Hall AJ et al. 2004. 15 Postweaning exposure to aflatoxin results in impaired child growth: a longitudinal study in 16 Benin, West Africa. Environ Health Perspect. 112: 1334-1338. 17 18 Groopman JD and Hall AJ and Whittle H and Hudson GJ and Wogan GN and Montesano R et 19 al. 1992. Molecular dosimetry of aflatoxin-N7-guanine in human urine obtained in The Gambia, 20 West Africa. Cancer Epidemiol Biomarkers Prev. 1: 221-227. 21 22 Hifnawy MS and Mangoud AM and Eissa MH and Nor Edin E and Mostafa Y and Abouel-23 Magd Y et al. 2004. The role of aflatoxin-contaminated food materials and HCV in developing 24 hepatocellular carcinoma in Al-Sharkia Governorate, Egypt. J Egypt Soc Parasitol. 34: 479-488. 25 26 IARC. 1993. Some naturally occurring substances -food items and constituents, heterocyclic

Food

  Victora CG, de Onis M, Lima RC, Blossner M, Clugston G. 2001. Worldwide 2 timing of growth faltering: implications for nutritional interventions. Pediatrics. 107: 75. 3 4 Turconi G and Guarcello M and Livieri C and Comizzoli S and Maccarini L and Castellazzi 5 AM et al. 2004. Evaluation of xenobiotics in human milk and ingestion by the newborn-an 6 epidemiological survey in Lombardy (Northern Italy). Eur J Nutr. 43: 191-197. 7 8 Turner PC, Moore SE, Hall AJ, Prentice AM, Wild CP. 2003. Modification of immune function 9 through exposure to dietary aflatoxin in Gambian children. Environ Health Perspect. 111: 217-Sylla A, Gong YY, Diallo MS, Sutcliffe AE, Hall AJ et al. 2005. Reduction in 13 exposure to carcinogenic aflatoxins by postharvest intervention measures in west Africa: a 14 community-based intervention study. Lancet. 365: 1950-1956. 15 16 Wang JS and Huang T and Su J and Liang F and Wei Z and Liang Y et al. 2001. Hepatocellular 17 carcinoma and aflatoxin exposure in Zhuqing Village, Fusui County, People's Republic of 18 China. Cancer Epidemiol Biomarkers Prev. 10: 143-146. 19 20 Weaver VM, Buckley TJ, Groopman JD. 1998. Approaches to environmental exposure 21 assessment in children. Environ Health Perspect. 106 Suppl 3: 827-832. 22 23 WHO. 1995. Physical status: the use and interpretation of anthropometry. Geneva 854. 24 25 WHO. 2003. Global strategy for infant and young child feeding. Geneva 26 27 Page 18 of 25 http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk Rasheed FN, Jawla MF, Hall AJ, Jansen LA, Montesano R. 1991. In-utero exposure to 1 aflatoxin in west Africa. Lancet. 337: 1602. 2 3 Willet W. 1990. Nutritional Epidemiology. New York Oxford University Press 15. 4 5 Zarba A, Wild CP, Hall AJ, Montesano R, Hudson GJ, Groopman JD. 1992. Aflatoxin M1 in 6 human breast milk from The Gambia, west Africa, quantified by combined monoclonal 7 antibody immunoaffinity chromatography and HPLC. Carcinogenesis. 13: 891-894.

Figure legends 1 2 Figure 1 .

 21 Figure legends

Table 1 .

 1 Descriptive maternal data.

			Food Additives and Contaminants		Page 20 of 25
	1
		Mother		% (Number)	Median (IQR)	Range
		AFM 1 (pg/ml)	negative	64% (250)
			positive	36% (138)	13.5 (10.3-21.4)*	5.6-5131*
		Lactation stage**			5 (2-8)	0.2-33.0
		Age (years)		100 (381)	25 (22-30)	15-47
		Number of miscarriages #	Total	100 (383)	-	-
			0	86 (331)
			1-3	14 (52)
		Number of children ##	Total	100 (384)	-	-
			1	28.4 (109)
			2-7	71.6 (275)
		Maternal BMI	Total	100 (336)	26.0 (24.0-28.5)	15.8-68.9
			<20	2.4 (8)
			20-<25	31.5 (106)
			25-<30	50.9 (171)
			>30	15.2 (51)
		Employed (%)	Total	100 (382)	-	-
			unemployed	89 (339)
			employed	11 (43)
		Socioeconomic status	Total	100 (384)	-	-
			LSES §	76.3 (293)
			HSES §	23.7 (91)
	2	*for positive samples, **number of months that mother has been breastfeeding index child
	3	# prior to index child, ## including index child
	4	§ (LSES) Low socioeconomic status, (HSES) High socioeconomic status
	5

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Table 2 .

 2 Descriptive infant data.

	Page 21 of 25				Food Additives and Contaminants
	1
		Child		% (Number) Median (IQR)	Range
		sex	boys	58 (227)	-
			girls	42 (159)
		age (months)			5 (2 to 8)	0.2 to 33.0
		HAZ		100 (322)	-1.49 (-2.63 to 0.02) -4.2 to 2.9
			> -2	64.2 (207)
			-3 to -2	17.4 (56)
			≤ -3	18.3 (59)
		WAZ		100 (375)	-0.45 (-1.47 to 0.43) -4.5 to 4.6
			> -2	85.6 (321)
			-3 to -2	9.3 (35)
			≤ -3	5.1 (19)
		WHZ		100 (351)	0.82 (0.17 to 1.66)	-2.3 to 4.8
			> -2	99.4 (349)
			-3 to -2	0.6 (2)
			≤ -3	0	(0)
	2	Malnutrition status is based on World Health Organization Guidelines.
	3	Z score less than -2 for HAZ (stunting), WAZ (being underweight) or WHZ (wasting) is defined
	4	as malnutrition, while less than -3 as severe malnutrition.

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Table 3 .

 3 Relationship between infant age and HAZ, WAZ and WHZ. -1.98 -0.14)* , ** -0.29 (-1.16 -0.78)* , # 0.37 (-0.20 -1.10) * , #

			Food Additives and Contaminants	Page 22 of 25
	1
		Age months	HAZ	WAZ	WHZ
		(quartiles)	Median (IQR)	Median (IQR)	Median (IQR)
		=<2 -0.73 (3-5 -1.67 (-2.87 --0.91) * , #	-0.53 (-1.49 -0.16) #	1.16 ( 0.37 -1.71) * , ##
		6-8	-2.25 (-3.00 --0.96)** , # -0.34 (-1.37 -0.33)	1.29 ( 0.65 -1.96) **
		>8	-1.29 (-2.55 -0.35)	-1.06 (-1.93 -0.13)*	0.74 (-0.11 -1.53) #, ##
			§ p= 0.001	§ p= 0.004	§ p <0.001
	2	§ p values based on Kruskal-Wallis One Way Analysis of Variance on Ranks
	3	* , ** Statistical significance p <0.001
	4	# , ## Statistical significance p <0.05

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children, and 14% had previously had a miscarriage. Most households (76%) belonged to LSES

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Emirates. Ann Trop Paediatr. 22: 3-9.

aromatic amines and mycotoxins. IARC Monogr Eval Carcinog Risks Hum 27.

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Edel Duffy

Aine Hearty

Albert Flynn

Sinéad Mccarthy

Michael Gibney

Keywords: Exposure assessment, packaging migration, children, modelling, packaging factors

published or not. The documents may come

The estimation of exposure to food packaging materials. 2. Patterns of intakes of packaged foods in Irish Children aged 5-12 years.

*Caution needs to be taken when using the probability of glass when it the only layer in contact with the food. In the NCFS respondents may have documented glass as the packaging used for the food and not documented the lid used for the packaging format.

Abstract

In the EU many assumptions are employed to calculate the intake of migrating chemicals from food packaging. However, very little is known about the actual intake of packaged food, the type of this food and also the type of packaging used for this food. The objective of the present study was to examine intakes of packaged food in children aged 5-12 years, to provide information on the types of food that are packaged and the type of packaging used. To do this a food consumption database, which also recorded information on packaging, was merged with a packaging database, which provided information on the contact layers of packaging. Foods were classified into EU Food categories according to European Council Directive EC 1985(EC 1985), which determined their food type (i.e. aqueous, acidic, alcoholic and fatty). The mean daily intake of all packaged food was 1195 g/day with an upper intake of 1959 g/day (97.5 th percentile) while the intake of food packaged in plastic was 993 g/day with an upper percentile of 1692 (97.5 th percentile). The mean daily intake of fat from all packaged food was 62 g/day with an upper intake of 100 g/day (97.5 th percentile). When this was investigated further, it was found that the mean fat intake from packaged "fatty" foods only, was 32g /day with an upper intake of 61 g/day (97.5 th percentile). The food that contributed most to fat intake was milk. As many food chemical intake assessments are moving towards probabilistic methods, probabilities of a food being packaged and the probability of the type of packaging used were determined. The probability of food being packaged was 0.88. Some foods that were not 100% packaged included fruit, vegetables, liquid beverages nonalcoholic (includes water) and bread. Probabilities were also derived for the packaging types used for food. From this study it can be concluded that not all the

Introduction

The market for packaged food continues to increase globally with the increase in consumption of pre-packaged food (Public Health Advocacy Institute, 2004). This increase in pre-packaged foods is partially due to the increased demand for convenience foods fuelled by the aging population, the diminished cooking skills of the typical consumer and the reduced time available for home preparation of meals.

For some items traditionally packaged in-store, for example meat, the demand for prepackaged fresh varieties of these foods is also growing [START_REF] Eilert | New packaging technologies for the 21 st century[END_REF]. The growth in the packaged food sector indicates that people may now be exposed to a larger variety of packaging materials and also to the chemical which can migrate from these packaging materials. However with the change in the types of packaging on the market, these changes, with some exceptions, have mostly been improvements in the way packaging acts as a barrier between food and the environment and also the interaction between the food and the packaging [START_REF] Hotchkiss | Food-packaging interactions influencing quality and safety[END_REF].

The safety of materials in contact with food is the subject of considerable regulation globally. One aspect of the safety assessment is the estimation of potential exposure to chemicals from the food contact material. When estimating the potential intake of any food chemical, the starting point should be with the crudest or most simple method [START_REF] Nutriscan | An evaluation of the methodologies for estimation of intakes of food additives and contaminants in the European Community[END_REF]. The EU safety assessment for chemicals used in food contact materials was developed in the 1960's by the Commission and subsequently adopted by the Scientific Committee for Food (SCF) (SCF, 2002). This safety assessment assumes that a person of 60 kg bodyweight will eat up to 1 kg of foodstuff packaged in the material of interest at a surface area to volume ratio of 6 dm 2 :dm 3 and that migration of the target chemical in the food contact material will occur at the maximum permitted level. Although more refined methods of exposure assessment have been proposed in the EU (MAFF 1999;[START_REF] Dionisi | Estimates of per capita exposure to substances migrating from canned food and beverages[END_REF][START_REF] Holmes | Dietary exposure to chemical migrants from food contact materials: A probabilistic approach[END_REF] this method continues to prevail and, realistically, it may be a sufficient first step method for the exposure assessment for many of the migrants present in food contact materials. However, over the past two decades a number of instances of public concern in relation to migrants from food contact materials have dictated the need for more refined and realistic exposure assessments. These instances included diethylhexyladipate from plasticised PVC films in the 1980s (MAFF 1987), contaminants from can coatings (MAFF 1997) and expoxidised soyabean oil in baby food [START_REF] Hammarling | Migration of epoxidised soya bean oil from plasticized PVC gaskets into baby food[END_REF] in the 1990s and semicarbazide from glass jars and bottles in very recent years (EFSA, 2003). Also with the future amendments to the regulations of plastic, more refined exposure estimates may be needed for the assessment of non-listed substances. The refined methods recently applied in the EU for the exposure assessment of food packaging migrants included the use of consumption data with total diet study data (MAFF, 1999), the use of per capita intake data or surface area to volume ratio data with migration data [START_REF] Dionisi | Estimates of per capita exposure to substances migrating from canned food and beverages[END_REF], and the application of probabilistic methods for the estimation of exposure to bisphenol A diglycidyl ether (BADGE), di-ethylhexyl adipate (DEHA) and styrene [START_REF] Holmes | Dietary exposure to chemical migrants from food contact materials: A probabilistic approach[END_REF].

In the US, a more refined first step approach is used for the estimation of exposure to food packaging migrants compared with the EU first step approach. The US FDA combine migration data with information on uses of food-contact articles that may contain the food contact substance (i.e. on the fraction of a person's diet likely to contact food contact articles containing the food contact substance) (FDA 2002). To do this, factors known as "consumption factors" and "food-type distribution factors" are used. The development of similar factors has been discussed in the EU (ILSI 1997). However, the present program of research intends to develop similar factors using data collected as part of an Irish National Children's Food Survey (IUNA 2005).

The issue of exposure assessment methodologies for food contact materials has been a topic of numerous industry and regulatory meetings. However there are few if any suitable data available in the EU on the proportion of foods consumed that are packaged or unpackaged, or even the packaging type used for these foods. The aim of the present study was to investigate the actual amount and probability of food consumed being packaged, to examine the types of foods that are packaged and to establish the types of packaging materials used for these foods.

Materials and Methods

The National Children's Food consumption Survey (NCFS) was a cross-sectional study of food and nutrient intakes of a representative sample of 594 Irish children aged 5-12 years (IUNA 2005). A 7-day weighed food record was used to measure food and beverage intakes. Respondents recorded the day, time, location and meal type for each eating occasion, along with a detailed description of the food, the weight of food and the packaging used for the food. The packaging used for the foods was also collected and forwarded to the coordinating centre where it was used to develop the Irish Food Packaging Database (IFPD) [START_REF] Duffy | Estimation of exposure to food packaging materials. 1. The development of a food packaging database[END_REF]. The methodology used to construct the IFPD and the content of this database is documented in a separate paper [START_REF] Duffy | Estimation of exposure to food packaging materials. 1. The development of a food packaging database[END_REF]. The respondents in the NCFS documented the generic packaging type, not specifically the contact layer, therefore the packaging database was developed to record the contact layer of the packaging. Polymer information for the plastics used as food contact materials was also documented if available. All references to packaging in this study apply to the packaging type used as the layer in contact with the food.

The NCFS consumption database and the IFPD packaging database were merged to form a database with complete information on foods consumed and the packaging used for these foods. The merger of the databases was completed in the software program SPSS® version 12.0.1 (SPSS Inc., Chicago, IL, USA) and this program was used for all analyses. As information in both databases was recorded at brand level of the food, brand codes were used to merge the datasets with care being taken to ensure that entries were also matched on unit weight and packaging type (some brand foods are available in different packaging formats and therefore care had to be taken to ensure the correct packaging information was matched with each eating event). The merger of the databases took place in a number of different stages. Since not all of the brand foods consumed in the NCFS had their packaging information recorded in the IFPD, information documented by the NCFS participants was used to assign exact packaging information to eating events of these brand foods. An eating event was the In addition to assigning packaging information to each eating event in the NCFS, each eating event was also assigned a EU food category code (i.e. aqueous, acidic, alcoholic or fatty). These EU food codes were assigned based on information from European Council Directive EC 1985(EC 1985) and the European Commission Food Contact Materials Note for Guidance (DG SCANCO, 2003). As some foods do not require migration testing these food were assigned as "Dry". The "Dry" group was used to code foods with no migration potential (e.g. cereals, sugar in solid form, dried pasta and rice) or frozen. A food group code was also assigned to all eating events.

Twenty-six food group codes were used to group foods of similar type and similar storage condition, for example "dried beverages" and "non-alcoholic liquid beverages".

Because the amount of food consumed was not always equal to the amount of food that was packaged, adjustment factors were applied to convert the weight of the food consumed back to the weight of the food as packaged (e.g. soup is packaged in the dried form however it is reconstituted with water before being consumed in the liquid form). Table 1 documents the type of foods to which adjustment factors were applied, the exact adjustment factors applied and the source of these adjustment factors. Each adjustment factor was multiplied by the weight of food consumed, documented in the NCFS, to get the amount of food consumed that was packaged. These factors were mainly for foods sold in the dried or powdered form. No factors were applied to foods to account for moisture loss during cooking.

[Insert Table 1 about here]

The database was analysed to provide information on the amount of food consumed that was packaged and specifically the amount of food consumed that was packaged in plastic. The intake of specific foods types (i.e. aqueous, acidic, alcoholic and fatty) was calculated, with further analysis completed on the intake of fat and fatty food.

Mean and percentiles were calculated for all intake parameters. Probabilities were calculated to provide information on types of foods that were packaged and unpackaged and also to provide information on the types of packaging used for packaged food. Packaged foods included all foods packaged by the producer, manufacturer or retailer for the customer while unpackaged foods were foods bought loose. There were 2.5 % (n=1808) eating events for which there was no packaging information available (i.e. packaged or unpackaged). When analyses were completed on the percentage of food consumed that were packaged versus unpackaged and on the types of food consumed these "unknown" entries were classified as being packaged to ensure conservative results.

Results

In this study the average daily intake of food (solids and liquids) was 1496 g/day (Table 2). The mean daily intake of packaged food was 1195 g/day with an upper percentile of 1959 g/day (97.5 th percentile). weight/day (97.5 th percentile) (these figures were derived by calculating the intake of food per kg body weight for each individual and then averaging this data to provide a mean intake of food per kg body weight for the sample population). When the figure for the intake of packaged food was analysed further, it was found that the mean daily intake of food packaged in plastic is 993g with an upper percentile of 1692g (97.5 th percentile).

To examine the types of food consumed in the NCFS as described in European

Council Directive EC 1985(EC 1985) (i.e. aqueous, acidic, alcoholic and fatty), each food consumed in the NCFS was classified as one of the four groups listed above or as "Dry" which was used to code foods with no migration potential (e.g. cereals, sugar in solid form, dried pasta and rice) or frozen. The mean daily intake of "acidic" food was 374 g/day, "dry" food 333 g/day, "aqueous" food 312 g/day and "fatty" food 177 g/day (Table 2). As the NCFS was completed on children no information was available on alcoholic foods.

As the intake of fat is often of concern in dietary surveys and exposure assessments of migrants from food packaging material, the mean daily fat intake was calculated at 63 g/day (Table 2). When the mean daily fat intake from packaged food was examined it was found to decrease marginally to 62g/day. The upper percentile of fat intake was 100 g/day with a maximum fat intake of 145 g/day from packaged foods. When fat intake from foods packaged in plastic alone was considered, the value fell to 49 + 14 g/day with the 97.5 th percentile at 78 g/day. The foods contributing to the fat intake from all packaged food are listed in descending order in Table 3. Milk is the largest contributor to fat intake with a mean fat intake from milk of 9.26g/day. Other foods contributing > 3g of fat per day are listed in Table 3. As described in the previous paragraph, fatty food intake was 620 g/day (97.5 th percentile) however the mean fat intake from fatty foods alone was only 32g/day (61g/day 97.5 th percentile).

[Insert Table 2 about here]

[Insert Table 3 about here] There were 72015 eating events in the NCFS. Of these eating events, 12%

(probability = 0.12) were unpackaged and 88% (probability = 0.88) were packaged 4). To achieve more in-depth figures for the probability of a particular food group being packaged or unpackaged, the probability was determined for a number of food groups. From the 26 food groups listed in Table 4, 18 groups had a probability of 1 of being packaged i.e. 100% packaged. Of the food groups that were not 100% packaged "fruit (fresh & dried)" had a 0.426 probability of being packaged, "Vegetables (fresh)" had a 0.58 probability of being packaged, "Liquid beverages non-alcoholic" had a 0.788 probability of being packaged (the high level of unpackaged eating events was mainly due to the consumption of tap water). Other groups that were not 100% packaged included "Bread", "Pies, pastries & cakes", "Processed foods and meals, chilled", "Sweet & savoury biscuits" and "Other (takeaways, eggs & nutritional supplements)".

[Insert Table 4 about here]

In addition to determining the probability of whether a food was packaged or unpackaged, probabilities were calculated for the type of packaging in contact with the food. Table 5a-d lists the probability of different types of packaging used for foods. Since more than one packaging material can be used for a food, Table 5a-d lists the probability of a material being used on it's own as a contact layer or in combination with other materials. For example the probability of plastic being used for "chocolate confectionary" is 0.722. However, plastic is also used in combination with metal and alloys for chocolate confectionary at a probability of 0.001 and therefore the total probability of plastic being used for chocolate confectionary is 0.723 (Table 5d).

[Insert Table 5a-5d about here]

Discussion

In order to refine the data currently used in the exposure assessment of food packaging migrants information was collected on the consumption of packaged foods and the types of materials used for these foods. A seven-day food diary was used in the NCFS to assess food intake and dietary habits of children in addition to packaging information. This method of collecting food consumption information is considered the gold standard in dietary assessment, since quantitative and accurate information on foods and beverages actually consumed is obtained through concurrent recording [START_REF] Löwik | Food consumption factors in relation to packaging materials in 8 European countries[END_REF]. As packaging information can also be ascertained through this dietary assessment methodology, there is no reason that this method cannot become the "gold standard" for the future collection of packaging information to directly link with food consumption data. Although this methodology has never been used in the past to collect food packaging information, it has been recognised as a valuable approach to collect data for the estimation of a chemical intake from food contact materials (Simoneau 2004).

This study was the first to analyse a food consumption database for packaging information and highlights some of the additional steps needed to prepare a database for packaging analyses. Before analyses all foods were classified as one of the food types outlined in European Council Directive EC 1985(EC 1985). The choice of food type depended on the type of contact the food had with the packaging. As it was not within the scope of this study to test the EU food category of every food consumed, EU Directive 85/572/EEC and the EU Notes for Guidance for food contact materials were used as reference documents for coding foods (DG SCANCO 2003). This necessitated some subjective decisions and some difficult options emerged. For example, yoghurts may be classified as "aqueous" or "acidic" based on different reference data sets. This discrepancy highlights the need for a more robust food classification system, which may be developed based on the physio-chemical properties of food. In addition to applying a EU food classification code, adjustments were made to correct for the amount of food that was actually packaged. This is necessary for analysing the amount of food consumed by individuals to ensure it represents the amount of packaged food consumed.

The conservative approach used in the EU to estimate the potential intake of migrants from food packaging material uses the assumption that 1 kg of packaged food is consumed per day, that this food is packaged in the material of interest and that migration occurs at the maximum level. It also assumes that the average weight of an adult is 60kg in order to compare potential exposure to a TDI. This assumption means that packaged food consumption is 16.6g/kg body weight/day (i.e. 1kg divided by 60kg). The principle underlying these parameters is that the average consumer will be well protected. This study demonstrates that a number of these assumptions are violated for children. As previously discussed in the literature, the intake of food by children far exceeds the assumption of 16.6g/kg bw/day [START_REF] Castle | Approaches to assess risk and assign priorities to chemicals used to make food contact materials[END_REF]Fantoni & Simoneau 2003;[START_REF] Hammarling | Migration of epoxidised soya bean oil from plasticized PVC gaskets into baby food[END_REF]. In a study by Castle et al. it was documented that the intake of food for infants (0-4 months) was 155g/kg bw/day and for small children 58 g/kg bw/day. These studies were not specifically documenting packaged food intake, rather total food intake. The present study demonstrated that the mean intake of packaged food per kg body weight (bw) was 39 g/kg bw/day for children aged 5-12 years. This increased intake of food per kg bw becomes an issue due to the fact that the specific migration limit (SML) for a substance is derived by applying the conventional factor of 60 (a 60kg person consuming 1kg of food) to the TDI value. Therefore materials and articles, which may comply with the SML, could actually cause the TDI to be exceeded for children. This was demonstrated with a case study on bisphenol A (BPA) completed by [START_REF] Castle | Approaches to assess risk and assign priorities to chemicals used to make food contact materials[END_REF], which demonstrated that the t-TDI for BPA could be exceeded for small children if migration levels were to approach the SML. Although the above scenario is theoretical and in practice the t-TDI is not exceed it highlights how exposures among children should be expected to be different than exposures among adults.

The mean daily food intake in this study was 1496 g/day, which is similar to US children's food intake of 1264g [START_REF] Mrdjenovic | Children eat what they are served: the imprecise regulation of energy intake[END_REF]. The mean daily intake of packaged food equal to 1195 g/day. If conservative figures were chosen to estimate potential intakes of packaged food, then intakes at the 97.5 th percentile (1959 g/day) could be used. Considering this data, the assumption currently used in the EU that 1kg of packaged food is consumed per day could not be viewed as conservative.

Although the results from this study are for children, in a national food consumption survey completed on Irish adults from 1997-1999 it was found that the average food intake per day was approximately 2.84 kg/day (IUNA 2001). This corresponds with food intakes in the US of 3 kg/day (FDA 2002) and the UK of 2.9 kg/day (Castle et al. in press), and is almost double the amount of food consumed by children. Therefore it could be hypothesised that the amount of packaged foods consumed by adults is in fact much greater than the 1195 g/day consumed by children, as their total food intake is greater. To investigate the intake of packaged food further, the intake of food packaged in plastic was examined. The mean daily intake of food packaged in plastic was 993 g/day with an upper percentile of 1692 g/day (97.5 th percentile). As comprehensive data was not collected on the polymers used for all the plastic contact layers, figures

were not developed for the probability or amount of food consumed that was packaged in each of the different polymers used as food contact materials. Therefore the assumption that 1 kg of food packaged in plastic used by the EU is correct for children but it is not a conservative figure and this may translate to a non conservative figure for adults due to their increased food intake. However when the EU conservative method assumes that the same polymer type is used for all foods packaged in plastic and that migration occurs at the maximum level, it is then that conservatism is introduced into the equation rather than the assumptions that individuals only consume 1kg of food packaged in plastic per day.

The 1kg of foodstuff currently used in the EU conservative calculation to estimate the intake of migrants could have an aqueous, acidic, alcoholic or fatty character. In this conservative exposure assessment, the total dose of migrant absorbed per day can only be derived from 1kg of food in contact with the plastic and that this kg is composed either of 1kg of fatty food or 1kg of one of the other types of food, but never the sum of the various types of food (SCF 2002). One issue with this assumption is that individuals do not consume 1kg of fat per day. A study completed by Löwik et al. showed that fat intake in g/day at the upper percentile of intakes (97.5 th percentile) ranged from 154-181g/day for the different countries studied [START_REF] Löwik | Food consumption factors in relation to packaging materials in 8 European countries[END_REF]. In 2002, the SCF reviewed and provided an opinion on the introduction of a "fat (consumption) reduction factor (FRF) for the estimation of exposure to a migrant from food contact materials" (SCF 2002). The SCF concluded that the consumption of 200g fat/person/day can be considered a realistic maximum intake and this opinion has been taken into account in the proposed Super Regulation for plastics. In the draft of this Super Regulation a "Fat Consumption Factors" (FRF) has been introduced when verifying compliance with specific migration limits for lipophilic substances contacting fatty foods. Based on the results of this study the figure of 200g fat/day would remain conservative for children as the 97.5 th percentile of fat intake from all foods was 101 g/day and from packaged food was 100 g/day.

However (EC 1985), it is the layer of food in contact with the packaging that determines the simulant required. For example, if a chocolate sweet is coated with a sugar shell then the choice of simulant is based on the sugar shell and not the chocolate. In the present study the consumption levels of these food types (aqueous, acidic, alcoholic or fatty)

were examined and it was found that the intake of fatty foodstuff from packaged food was 342 g/day (97.5 th percentile). However the mean fat intake from fatty foods alone was 32 g/day. This highlights that the actual fat intake from foods that require a fatty simulant (olive oil) is much lower (almost 50%) and that by introducing a FRF based on fat intake will still lead to a conservative result. The highest contributor to fat intake was milk (mean daily intake = 9.26g/day). In EU Directive 85/575/EEC milk is classified as an aqueous food. Distilled water is not the most appropriate simulant for milk (Tawfik & Huyghebaert, 1998), and another study found that the fat content of milk does not significantly affect migration into milk [START_REF] Castle | Evaluation of the scientific basis of EC Directives 82/711/EEC, 85/575[END_REF]. This discrepancy had been addressed in the new amendments to the plastic regulations where 50% ethanol has been proposed as a suitable simulant for milk.

It should also be noted that the intake of dry foodstuffs (including frozen food) was 333 g/day (mean) with an upper percentile of 620 g/day (97.5 th percentile). According to the current legislation no migration testing is required for dry foodstuffs. However in a study of this issue, it was found that migration was seen in all dry foods tested except for sugar and it was recommended that the packaging for dry foods should not automatically be exempted from tests with simulants [START_REF] Castle | Evaluation of the scientific basis of EC Directives 82/711/EEC, 85/575[END_REF]. Other studies have also shown the migration of packaging migrants into dry foods (Parry and Aston 2004;Summerfield and Cooper 2001). This may warrant further consideration due to the high level of consumption of these products.

A method previously applied for the exposure assessments of other food additives and also environmental risks is probabilistic exposure assessments. In recent years this method has been used for the estimation of exposure to food packaging migrants [START_REF] Holmes | Dietary exposure to chemical migrants from food contact materials: A probabilistic approach[END_REF]. If probabilistic methods are used to estimate exposure to migrants from food packaging materials, information is needed on a number of variables, such as the probability of the food being packaged and if packaged the type of material used. Information is also needed on the presence of migrants in these materials and the migration of these substances into the food. In this paper, the first is the probability of the food being packaged. If it is not packaged then there is no need to include this item in an exposure calculation. In this study it was obvious for most food items if they were packaged or not but for others it proved more difficult.

For example, if ham presented loose at a deli counter was then packaged before purchasing could this be classified as packaged? For the purposes of this study, packaged items included all items packaged by the producer, manufacturer and retailer for the consumer e.g. deli counter items, meats from butchers etc. This did not include foods packaged by the consumer in-store i.e. loose fruit and vegetables. When analysis was completed on this study it was found that 88% of all eating events were packaged. When more detailed analyses were completed the food groups that were not 100% packaged included fruit, vegetables, liquid beverages non-alcoholic (includes tap water), pies, pasties and cakes and bread. These foods are similar to foods identified in a study completed in the UK on food items that are unpackaged This is also the first study to present probabilities for the type of packaging used for individual food groups. The food grouping system used in this study was chosen to represent similar foods with similar storage conditions. However the database can easily be restructured if data was needed on other food groups or more specific details were needed for the food groups already outlined in Table 4. Therefore if a probabilistic exposure assessment was to be completed based on the results of this study, the probability of a food being packaged is 0.88. If the food is packaged, then table 5a-d could be used to determine the probability of the packaging type. To progress further in a probabilistic exposure assessment, data on the market share of specific polymers could be used to develop probabilities for the type of polymer used.

Industry or laboratory data would then be needed to define the probability and amount of the migrant present in the contact layer or in the food. If no migration data were available then the maximum migration limit could be assumed or migration modelling software could be used to generate values for the likely migration. Although all the data needs for a probabilistic exposure assessment were not collected in this study, two of the data needs regarding the probability of food consumed being packaged and the type of packaging used for these foods have been identified and these two data parameters have been identified in the past as being the "bottle neck" in the exposure assessment calculation [START_REF] Gibney | How to obtain realistic estimates of exposure from food packaging material[END_REF]).

If the methodology used in this study for the collection of food consumption data and packaging data is replicated in other European surveys, the data needed for the refinement of the exposure assessment to food packaging migrants can be readily obtained, which will then lead to more realistic and representative exposure assessments.

F

  individual food or dish at a particular time point either alone or as part of a meal.Eating events of homemade recipes accounted for approximately 3% of all eating events in the NCFS. Homemade recipes did not include pre-prepared meals/dishes sold at retail level or foods cooked using methods that may have employed a small quantity of another ingredient e.g. onions fried in corn oil. If a homemade recipe was consumed during the NCFS participants were asked to record the ingredients used in the recipe and also the packaging used for these ingredients in a separate section of the diary and this information was used to construct a recipe database. Packaging information was assigned to recipes based on the level of information present in the recipe database. If packaging information was present for one ingredient then this packaging information was used. If the same type packaging was used for one or more ingredients (e.g. flour in paper and castor sugar in paper) then this packaging type was used. If a different type of packaging material was recorded for ingredients then the packaging material for the ingredient with the largest recipe fraction and most migration potential was assigned. If packaging information was not recorded in the recipe database then an assumption was made for the type of packaging used for the ingredients.

  are addressed. The first question to answer in an exposure calculation

  (i.e. fruit, vegetable, bread, pastries)(FSA 2003). However in the UK study unpackaged items included meats and cheese as their definition of what constituted unpackaged included products sold loose or packaged in store and therefore differed from the definition of what constituted an unpackaged item used in our study.

Table 1 . Adjustment factor to convert the amount of food as consumed to the amount of food as packaged.

 1

	Food

Table 2 . The amount of food consumed (g/day) according to packaging status and food type.

 2

	Percentiles

Table 3 . Mean daily fat intake (g/day) from packaged foods per food group with standard deviations (SD) for 594 children aged 5-12 years.

 3

	Food	Mean	SD
	Milk	9.26	6.93
	Butter & spreads	5.51	5.26
	Chocolate confectionary	5.23	4.43
	Savoury snacks	4.33	3.08
	Chips & roasted potatoes	3.89	3.04
	Cheese	3.69	3.16
	Savoury & convenience meals	3.37	3.25
	Biscuits & cakes	3.15	2.28
	Processed meat & meat products	3.05	1.86

Table 4 . Description and frequency of packaged and unpackaged foods in National Children's Food Survey. Page 4 of 28 http

 4

	Food Additives and Contaminants

://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

Table 5a . Probability of glass being used as a packaging material for food groups*

 5a

				Glass
			Glass	Glass
			&	&	Total
	Food Group	Glass	Metal & Alloys	Plastic	Glass
	Chocolate confectionary				0
	Sugar confectionery			0.001	0.001
	Ice-cream				0
	Jams and spreads	0.021	0.531	0.394	0.946
	Crisps, nuts and snacks				0
	Sweet & savoury biscuits				0
	Pies, pastries and cakes				0
	Bread				0
	Bakery products				0
	Cereal and cereal products				0
	Dry Rice, pasta and noodles				0
	Fish & seafood (fresh & frozen & processed)		0.002		0.002
	Fresh meat (chilled & frozen)				0
	Processed meat				0
	Cheese & cheese products				0
	Dairy Products				0
	Oils	0.333	0.056		0.389
	Fruit (fresh & dried)				0
	Vegetables (fresh)				0
	Liquid beverages non-alcoholic	0.001	0.004		0.005
	Dried beverages tea and coffee	0.008		0.033	0.041
	Processed foods and meals, ambient moist	0.005	0.281	0.019	0.305
	Processed foods and meals, chilled		0.018		0.018
	Processed foods and meals, frozen		0.001		0.001
	Processed foods and meals, dehydrated		0.003	0.018	0.021
	Other (eggs, nutritional supplements & takeaway food)	0.027	0.013	0.081	0.121

Table 5b . Probability of metal & alloys being used as a packaging material for food groups.

 5b

						Paper & Board
					Paper & Board	Paper & Board	Total for
						&	&	Paper &
	Food Group			Paper & Board	Metal & Alloy	Plastic	Board
	Chocolate confectionary			0.076		0.003	0.079
	Sugar confectionery			0.609			0.609
	Ice-cream			0.211		0.001	0.002	0.214
	Jams and spreads F Crisps, nuts and snacks o r Sweet & savoury biscuits		0.014 0.017			0.013	0 0.014 0.03
	Pies, pastries and cakes Bread Bakery products Cereal and cereal products	P e e r	0.237 0.394 0.905 0.04		0.01	0.137 0.009	0.384 0.403 0.905 0.04
	Dry Rice, pasta and noodles			0.18			0.18
	Fish & seafood (fresh & frozen & processed)	R	0.106			0.106
	Fresh meat (chilled & frozen)		e 0.004			0.004
	Processed meat Cheese & cheese products Dairy Products Oils		0.013 v i 0.005 e 0.126 w	0.001	0.002 0.063	0.015 0.006 0.189 0
	Fruit (fresh & dried) Vegetables (fresh) Liquid beverages non-alcoholic Dried beverages tea and coffee Processed foods and meals, ambient moist		0.045 0.437 0.001 0.793 0.002	0.111 l 0.001 O n 0.015 y	0.156 0.438 0.001 0.808 0.002
	Processed foods and meals, chilled		0.012		0.009	0.021
	Processed foods and meals, frozen		0.058		0.002	0.001	0.061
	Processed foods and meals, dehydrated		0.402		0.076	0.478
	Other (eggs, nutritional supplements & takeaway food)	0.559		0.002	0.002	0

.563 Table 5c. Probability of paper & board being used as a packaging material for food groups.

	F o r
	P
	e
	e r
	R
	e
	v i e
	w
	O n l
	y

Plastic Food Group Plastic Plastic & Glass Plastic & Metal & Alloys Plastic & Paper Total for Plastic

	Chocolate confectionary	0.722		0.001		0.723
	Sugar confectionery	0.376	0.001			0.377
	Ice-cream	0.786			0.002	0.788
	Jams and spreads	0.052	0.394			0.446
	Crisps, nuts and snacks	0.984				0.984
	Sweet & savoury biscuits	0.957		0.001	0.013	0.971
	Pies, pastries and cakes	0.586		0.014	0.137	0.737
	Bread	0.596			0.009	0.605
	Bakery products	0.095				0.095
	Cereal and cereal products	0.96				0.96
	Dry Rice, pasta and noodles	0.818				0.818
	Fish & seafood (fresh & frozen & processed)	0.622				0.622
	Fresh meat (chilled & frozen)	0.992				0.992
	Processed meat	0.969		0.001	0.002	0.972
	Cheese & cheese products	0.89		0.059		0.949
	Dairy Products	0.557		0.253	0.063	0.873
	Oils	0.611				0.611
	Fruit (fresh & dried)	0.835			0.111	0.946
	Vegetables (fresh)	0.561				0.561
	Liquid beverages non-alcoholic	0.979				0.979
	Dried beverages tea and coffee	0.06	0.033			0.093
	Processed foods and meals, ambient moist	0.295	0.019			0.314
	Processed foods and meals, chilled	0.94		0.012		0.952
	Processed foods and meals, frozen	0.935		0.001	0.001	0.937
	Processed foods and meals, dehydrated	0.464	0.018	0.012		0.494
	Other (eggs, nutritional supplements & takeaway food)	0.166	0.081	0.133	0.002	0

.382 Table 5d. Probability of plastic being used as a packaging material for food groups.

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Estimation of exposure to food packaging materials 2. Patterns of intakes of packaged foods in Irish Children aged 5-12 years.

	E. Duffy 1 , A.P. Hearty 1 , A. Flynn 2 , S. McCarthy 1 and M. J. Gibney 1
	1 Institute of European Food Studies, Department of Clinical Medicine, Trinity Centre
	for Health Sciences, St. James's Hospital, Dublin 8, Ireland.
	2 Department of Food and Nutritional Sciences, University College, Cork, Ireland.

  when classifying foods according to European Council Directive EC 1985

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  Fantoni L, Simoneau C. 2003. European survey of contamination of homogenized baby food by epoxidized soyabean oil migration from plasticized PVC gaskets. Food Additives and Contaminants 20, 11, 1087-1096. Food and Drug Administration (FDA) 2002. Guidance for Industry: Preparation of food contact notifications and food additive petitions for food contact substances: chemistry recommendations. Final Guidance. Center for Food Safety and applied Parry SJ, Aston DSJ. 2004. Migration of inorganic contaminants into dry food from packaging made from recycled paper and board. Food Additives and Contaminants 21(5):506-511. Public Health Advocacy Institute 2004. Obesity as an Epidemic. Available from: http://www.phaionline.org/projects_obesity_epidemic.php. Accessed 2005 Dec 13. Simoneau C. 2004. Exposure to chemicals from food contact materials. European Commission DG Joint Research Centre, Institute for Health and consumer Protection, /www.jrc.cec.eu.int/more_information/download/contmat2.pdf. Accessed 2005 Dec 15. Summerfield W, Cooper I. 2001. Investigation of migration from paper and board into food-development of methods for raid testing. Food Additives and Contaminants 18:77-88.

	o r F o r Nutrition. Office F o r F o r Physical and Chemical of F o r	Food Exposure Additive Unit,	Safety. Ispra.	Available Available	from: from:
	P e e r R e v i e P e e r R e v i e P e e r R e v i e P e e r R e v i e P e e r R e http:/Tawfik MS, Huyghebaert A. 1998. Polystyrene cups and containers: styrene migration. Food Additives and Contaminants 15(5):592-59. v i e
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