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Variation and modifying factors of the exposure to lead and cadmium based on an epidemiological study
The Science of the Total Environment, 84 (1989) 1 12 Elsevier Science Publishers B.V., Amsterdam - - Printed in The Netherlands
1
VARIATION A N D MODIFYING FACTORS OF THE EXPOSURE TO LEAD AND CADMIUM B A S E D ON AN EPIDEMIOLOGICAL STUDY
K. LOUEKARI
Ministry of Agriculture and Forestry, Food Research Program, Viikki 22 A, SFo00710 Helsinki (Finland) U. UUSITALO and P. PIETINEN
National Public Health Institute, Department of Epidemiology, Mannerheiminte 166, SF-00280 Helsinki (Finland) (Received March 15th, 1988; accepted January 24th, 1989)
ABSTRACT Exposure to cadmium and lead was studied using a dietary survey. Data for 1348 individuals aged 25-64 years were collected using 3-day food records. In addition to the dietary intake of heavy metals, the effect of the following were also analyzed: smoking frequency, place of residence, occupation and age. Total cadmium and lead exposure was estimated by calculating intake from food plus that from inhalation, i.e. from urban air and smoking. Heavy smoking increased the cadmium exposure three-fold. The distribution curve of total cadmium exposure was bimodal due to the additional exposure caused by smoking. The distribution curve of the lead and cadmium exposure from food was also skewed, being mostly influenced by food intake. Contaminated urban air slightly increased the total exposure to lead. Occupation had a minor effect on the exposure to both metals. Housewives and retired persons were the least exposed groups. The distribution pattern and wide range of heavy metal exposure should be taken into account in risk assessment for contaminants in food. The additional exposure to cadmium and lead from smoking and from air and water should be considered.
INTRODUCTION
The intake of food contaminants is estimated in order to evaluate the safety of the food supply. A variety of methods are available for estimation of intake; many of them originate from dietary surveys and have recently been adopted in food toxicology. Comprehensive reviews on the methods have recently been p r e p a r e d [1-3]. I n s o m e c o u n t r i e s , t h e a v e r a g e i n t a k e o f l e a d a n d c a d m i u m is r e l a t i v e l y c l o s e to t h e p r o v i s i o n a l t o l e r a b l e w e e k l y i n t a k e s ( P T W I ) s u g g e s t e d b y t h e W o r l d H e a l t h O r g a n i s a t i o n (WHO). F o r e x a m p l e , i n t h e F e d e r a l R e p u b l i c of G e r m a n y , t h e e s t i m a t e of t h e i n t a k e o f l e a d a n d c a d m i u m is 40 a n d 70% of P T W I v a l u e s , r e s p e c t i v e l y [4]. H o w e v e r , t h e i n t a k e o f h e a v y m e t a l s , a n d a l s o t h a t of o t h e r c o n t a m i n a n t s of food, v a r i e s c o n s i d e r a b l y . V a r i a t i o n c a n b e d e s c r i b e d u s i n g t h e 90th p e r c e n t i l e o r t h e r a n g e o f i n t a k e . T h e s e d a t a a r e
0048-9697/89/$03.50
© 1989 Elsevier Science Publishers B.V.
included in some recent reports of intake studies, since they provide essential information for risk assessment [5-8]. Variation of intake of food contaminants is a result of different food consumption habits and varying types of environmental contamination [9-11]. Food consumption is dependent on several socio-economic and physiological variables: for example, age and occupation are determinants of energy requirement. In addition, other routes of exposure, especially respiratory intake, affects the total body burden. Smoking and urban air increase the total exposure to lead and cadmium and this should be considered when the significance of food contamination by these elements is assessed. How should the variation of total intake and the intake of groups at risk be monitored in order to regulate the maximum allowed levels of contaminants in food adequately ? There are relatively few publications on the variation of intake of food contaminants. In most cases, the mean intake and often also the 90th percentile is reported. Obviously there is a need to study: (i) the applicability of epidemiological data for estimation of the variation of heavy metal intake and the total exposure; (ii) the effect of independent factors (age, profession, smoking, area of residence) to the total exposure; (iii) the distribution pattern (based on individual data) of the exposure for the population. METHODS
Subjects The FINMONICA project conducted by the National Public Health Institute is part of a multicenter project coordinated by WHO. The 1982 FINMONICA risk factor survey on cardiovascular diseases was carried out on a random sample of persons aged 25-64 years in the provinces of North Carelia and Kuopio in eastern Finland and in Turku-Loimaa in south-western Finland. These study sites were selected because a large difference between the areas in the incidence of cardiovascular diseases has been observed. The total number of participants was 6523. The dietary survey consisted of a subsample: persons born between the 7th and 12th of each month were asked to keep food records at home. Of those eligible, 80% completed the food record and thus the final number of participants was 1348 persons (653 men and 695 women).
Food consumption data and intake of lead and cadmium through food In the first population survey of FINMONICA, risk factor data as well as dietary data were collected. The present analysis is based on this survey carried out in 1982 in eastern and south-western Finland. Data on food consumption was collected on the basis of a three day food record. Detailed information was obtained on the type and amount of food
TABLE 1 Concentration of lead in Finnish drinking water, some food items and air Sample
n
Ref.
( 0.5-14.2
863
14
2-10
48 30 48 5
15 15 15 13
Concentration Average _+ SD
Tap water
(pg1-1)
Wheat flour Potatoes Pork meat Cabbage
Ozgkg -1)
Urban air
~ g m -3)
0.6 11 + 1 11 _+ 2 13 + 3 10 0.3"
Range
< 0.1~0.95
300
16,17
In the middle-sized cities.
consumed by the subjects during three successive days. The participants of the survey received oral and written instructions and forms for keeping the food record. Completed records were checked and coded in the National Public Health Institute. Tables, especially compiled for FINMONICA, were used to convert household measures into grams [12]. The cadmium and lead content of foods used in calculations were obtained from a comprehensive mineral element study of Finnish foods, consisting of the analysis of 1948 samples [13]. The sampling covered mills, slaughterhouses, dairies and various types of retail outlet. Many samples consisted of 10-40 subsamples, which were collected to be representative of the possible seasonal and local variation of food composition. Some average concentrations and ranges of this study, as well as other studies, are given in Tables 1 and 2. Intake of lead and cadmium from foods was calculated using food composition data and computer programs developed in the Department of Nutrition, University of Helsinki [20]. Detailed results of the 1982
TABLE 2 Concentration of cadmium in Finnish drinking water, some food items and air Sample
Concentration Average + SD
Tap water
(/zg 1 l)
Wheat flour Potatoes Pork meat Cabbage
~ g k g -1)
Urban air
(/zgm 3)
0.05 40 48 _+ 10 3 5 1
n
Ref.
863
14
1-17 5-10
14 44 48 5
15 13 15 13
0.~9
120
19
Range < 0.5-0.66 30-50
FINMONICA dietary survey have been published [21]. The distributions of the lead and cadmium exposure and the total exposure have not been considered previously.
Intake from ambient air, smoking and drinking water There were two major routes of cadmium exposure in the survey population: through cigarette smoking and from food. The total amount of cadmium absorbed by subjects was calculated by assuming that 5% of the cadmium via food is absorbed and that 0.05 #g of cadmium is absorbed from one cigarette [22-24]. The absorbed amounts of cadmium via both routes were added to provide the total exposure. In addition to the lead intake from food, the urban population is exposed to lead-polluted air. Monthly averages of air-lead content were available only for Kuopio, but not for Turku, the other city participating in the study [17]. Based on these and other air quality monitoring data for moderately contaminated Finnish urban areas outside the study, it was approximated that the lead content of the air of the two middle-sized cities of the study area (Turku and Kuopio) is on average 0.3gg m -3 [16,17]. This contributes 5.4pg day -1 to the total lead exposure, using a respiratory volume of 18 m a day- 1. This estimate of respiratory volume is based on modifications of data in current textbooks [25] and consists of three periods of 8 h: 8 m 3 during non-physical work, 7 m 3 during leisure and 3 m 3 during sleep. The amounts of lead entering humans from food and air were added to provide the total exposure. Biological availability of lead is strongly dependent on the chemical form and particle size; there are no conclusive estimates about absorption [26]. Drinking w a t e r also contributes to exposure from heavy metals, which has been estimated to be 0.1~g day -1 for cadmium and 1.2ttg day 1 for lead in Finland. This is a minimal proportion of the total intake and it has been estimated t h a t only for 5% of waterworks does the drinking water contribute > 5% to the total intake of lead and cadmium [14]. It was not possible to calculate local intakes of lead and cadmium from drinking water, since the tap water study mentioned above was separate from the FINMONICA project and the sampling areas were different. Moreover, no geographical variation, which could be explained by quality of soil or local air pollution, has been found. The materials constituting the water pipes and distribution systems seem to be the origin of elevated heavy metal concentrations in tap water (Tables 1 and 2). This epidemiological study covers the inter-individual differences and differences between areas in food consumption and smoking, but not local data on the contamination of air and drinking water.
Modifying factors The factors affecting lead and cadmium intake selected from the risk factors
5 of the F I N M O N I C A s t u d y were smoking, age and o c c u p a t i o n . The s m o k i n g f a c t o r was classified as follows: Class 1 Non-smoking 2 Occasional smoking 3 Moderate smoking 4 Heavy smoking
C i g a r e t t e s per day 0 1-10 11-25 26-80
Age was also classified and i n t a k e s were estimated at 10-year intervals for b o t h sexes. O c c u p a t i o n was classified into the following categories: farmers, blue-collar workers, white-collar workers, students, housewives, retired and unemployed. Significance of differences b e t w e e n g r o u p s was tested by analysis of v a r i a n c e and D u n c a n ' s multiple r a n g e test. RESULTS AND DISCUSSION H e a v y s m o k i n g caused a three-fold exposure to c a d m i u m c o m p a r e d with the a v e r a g e n o n - s m o k e r (Table 3). A b o u t 5% of adult men smoked > 25 c i g a r e t t e s a day. In this g r o u p the a m o u n t of absorbed c a d m i u m was estimated to be 2.6 gg d a y - l ; the absorbed a m o u n t of c a d m i u m for the a v e r a g e n o n - s m o k e r was only 0.8 pg d a y - ' . Differences between the g r o u p s presented in Table 1 are s t a t i s t i c a l l y significant (p < 0.01). This is in a g r e e m e n t with the o b s e r v a t i o n t h a t the m e a n level of c a d m i u m in blood of c u r r e n t smokers is a p p r o x i m a t e l y four-fold the m e a n of n o n - s m o k e r s [27]. TABLE 3 Effect of smoking on the total exposure to cadmium, calculated as absorbed amount of cadmium. It was assumed that 5% of the cadmium via food is absorbed and that 0.05/~gof cadmium is absorbed from one cigarette Sex
Smoking cigarettes day- i
Total absorbed cadmium ~g day 1) Mean
SD
n
Men
0 (non-smoking) 1-10 (occasional) 11-25 (moderate) 26-80 (heavy) All
0,80 1.07 1.69 2.58 1.11
0.24 0.26 0.30 0.69 0.56
405 63 147 29 644
Women
0 (no smoking) 1 10 (occasional) 11-25 (moderate) 26-80 (heavy) All
0.64 0.94 1.48 2.33 0.74
0.18 0.25 0.25 0.28 0.32
566 69 52 3 690
All differences between groups are statistically significant (p < 0.001).
Urban air had a slight, but statistically significant, effect on the total lead exposure in this study. In the present study the mean lead exposure (59.4 pg day t) of urban people was only 3-4#g day 1 higher than the average lead exposure of rural people (56.1#g day-t). However, no accurate results of air lead analysis were available. The present results are based on the approximation that in relatively small cities ( ~ 75000 inhabitants) in the study areas the lead content of air is 0.3/~g m -3 [17]. Obviously in many urban areas in industrialized countries this concentration of lead in ambient air is exceeded and should be considered together with oral exposure when lead-induced risk is assessed. The distribution curve of lead and cadmium intake via food was skewed in the present study (Figs 1 and 2). This was due to a similar distribution pattern for food consumption among the participants of the study. High food consumption was more common than food consumption below nutritional requirements. This observation suggests that the average intake of food contaminants is not an adequate basis for risk assessment, since the intake of certain consumer groups is two or three times higher than the average intake. The distribution pattern of total absorbed cadmium (from food and smoking) was more skewed (Fig. 3) than the curve of cadmium intake from food. The curve was slightly bimodal. A small secondary peak at 1.5pg day -t (absorbed amount) represents moderate smokers, who are more abundant than occasional smokers in this study (Table 3). Age has a significant effect on the intake of lead and cadmium from food. Lead and cadmium intake in the oldest (60-64 years) age group was significant150 14-0 130 120
7 / / / / / / / / / / / / / / / / / /
110 1 O0 9O E
80
0"
70 6O 50 4O 30 2O 10
w / / / /
0
I
2
4
6
8
10
12
I4
16
18
Intake
Fig. 1. Distribution of cadmium intake from food.
l
l
20
l
l
]
22
(;Jg/d)
l
I
I
24
I
I
26
l
,777-
l
28
30
32
34
300 28O 260 240 220 // // // // // // // // // // // // // // // // // //
2OO 18Q c
16Q
g-
14-0 120 1QO 8O 6O 40 2O 0 0
15
25
// // //
/A //1 /A
// x ,, z/ //
/A //1 / f //
~ //
//
//
//
//
/ /
/ /
//
//
/ /
//
//
//
//
/ /
/ /
//
//
//
//
//
/ /
//
//
/ /
// //
//
/ /
/ /
//
//
//
//
//
//
//
//
/I /,;
// //
// / /
/
/
i
I
35
45
/
55
65
75
85
95
105
115
125
135
14-5 1 5 5
(pg/d)
Intake
Fig. 2. Distribution of lead intake from food.
220 200 180 160 140
c
120
,Y
100 80 60 40
0
_FI I
I
I
i
0.5
i
i
i
i
i
i
I Exposure
i
t
i
i
i
I .5 (absorbed
i
~
i
i
i
2 amount)
i
i
J
i
2.5
i
i
i
i
3
i
~ I I T ~ 3.5
)Jg/day
Fig. 3. Distribution of total cadmium exposure. Includes the intake from food and smoking.
8
TABLE 4 Lead and cadmium intake ~ g day -1) according to age group Sex
Age
Lead
Cadmium
n
Men
25 29 30-39 40-49 50-59 60-64 All
62 69 62 55 51 61
17 17 16 14 13 16
56 193 141 186 77 653
Women
25-29 30-39 4049 50-59 60-64 All
53 54 49 49 43 50
13 13 13 13 12 13
53 178 183 188 93 695
Statistically significant differences between groups (both sexes): Cadmium intake 60-64 vs 50-59 p < 0.01 60~4 vs others p < 0.001 25-29 vs 50-59 p < 0.01 30-39 vs 40-49 p < 0.01 30-39 vs 50-59 p < 0.001
Lead intake 60-64 vs 50-59 p < 0.01 60-64 vs others p < 0.001 30-39 vs 40-49 p < 0.001 30-39 vs 50-59 p < 0.001
l y l e s s ( p = 0.0001-0.0038) t h a n i n t h e o t h e r f o u r a g e g r o u p s ( T a b l e 4). L e a d i n t a k e o f t h e 30-39 y e a r s a g e g r o u p w a s s i g n i f i c a n t l y h i g h e r ( p < 0.001) t h a n the 40-49 and 50-59 year age groups. Cadmium intake of the 50-59 years age g r o u p w a s s i g n i f i c a n t l y s m a l l e r ( p = 0.001-0.0080) t h a n t h o s e o f t h e f i r s t t w o a g e g r o u p s (25-29 a n d 30-39). I n c o n t r a s t , t h e c a d m i u m i n t a k e p e r 1000 k c a l w a s e s t i m a t e d t o b e s i g n i f i c a n t ly s m a l l e r i n y o u n g e r t h a n i n e l d e r l y a g e g r o u p s . H o w e v e r , t h e r e w e r e n o s i g n i f i c a n t d i f f e r e n c e s b e t w e e n a g e g r o u p s i n t h e l e a d i n t a k e p e r 1000 k c a l . T h i s s u g g e s t s t h a t t h e a m o u n t o f f o o d c o n s u m e d is t h e m a j o r f a c t o r c o n t r i b u t i n g t o t h e d i f f e r e n c e s o b s e r v e d i n l e a d i n t a k e b e t w e e n a g e g r o u p s ( T a b l e 4). T h e s t a n d a r d d e v i a t i o n o f l e a d a n d c a d m i u m i n t a k e i n a g e g r o u p s is r a t h e r s m a l l , i.e. < 26 a n d 5 # g d a y -1, r e s p e c t i v e l y . I n a d d i t i o n t o a g e , t h e i n d i v i d u a l f o o d consumption habits, as well as varying demand of energy, causes variation of the intake of food contaminants. Occupational status also seems to affect the intake of lead and cadmium f r o m food. H o u s e w i v e s a n d r e t i r e d p e r s o n s h a d l o w e r c a d m i u m a n d l e a d i n t a k e c o m p a r e d w i t h o t h e r g r o u p s ( T a b l e 5). H o w e v e r , s i m i l a r d i f f e r e n c e s w e r e n o t o b s e r v e d w h e n c a d m i u m a n d l e a d i n t a k e p e r 1000 k c a l w e r e a n a l y z e d . T h i s suggests that age and sex partly explain the differences stated above. Whitec o l l a r w o r k e r s h a d a h i g h e r l e a d i n t a k e p e r 1000 k c a l t h a n f a r m e r s a n d b l u e c o l l a r w o r k e r s (p < 0.001). W h i t e - c o l l a r w o r k e r s , h o u s e w i v e s a n d r e t i r e d
TABLE 5 O c c u p a t i o n a l s t a t u s and i n t a k e of cadmium and lead from food Occupational status
1. F a r m e r s 2. Blue-collar workers 3. White-collar workers 4. S t u d e n t s 5. H o u s e w i v e s 6. Retired p e r s o n s 7. Unemployed p e r s o n s
Cadmium i n t a k e
Lead intake
Mean
SD
Mean
SD
15.1
5.0
58.0
24.1
212
15.0
5.1
58.4
24.4
302
13.9 16.8 12.5 12.4 14.7
4.2 6.3 3.8 3.4 4.5
55.8 68.2 45.7 48.7 52.2
21.8 26.4 19.8 21.3 21.2
528 9 99 155 18
Statistically significant differences b e t w e e n g r o u p s (both sexes): Cadmium lvs3p lvs5p lvs6p 2vs3p 2vs5p 2vs6p 3vs5p 3vs6p 4vs5p 4vs6p
intake < 0.001 < 0.001 < 0.001 < 0.01 < 0.001 < 0.001 < 0.01 < 0.001 < 0.01 < 0.(}1
Lead intake lvs5p < 0.001 lvs6p < 0.001 2 v s 5 p < 0.001 2 v s 6 p < 0.001 3 v s 5 p < 0.001 3 v s 6 p < 0.001 4vs5p < 0.01
persons had a significantly higher intake of cadmium per 1000 kcal than farmers and blue-collar workers. This suggests that greater demand for energy is provided by eating foods with low cadmium concentration, i.e. meat and dairy products. Students (n = 9) had the highest intake of lead and cadmium (72 and 17#g day 1, respectively), but the difference was statistically significant only when compared with housewives and retired persons (p < 0.01). However, the size of the group is too small for any definite conclusions regarding students. It should be noted that the lead and cadmium intake of individuals is calculated using average values of the lead and cadmium content of food items. However, heavy metal concentrations in food items vary due to varying deposition of pollutants, concentration of metals in fertilizers and soil conditions, although the most important point sources of emissions are far from the study areas. The composition of the food actually eaten is different for ali individuals. To take this into consideration would require determination of heavy metals in duplicate meal samples of every individual in the study. For the present study cohort, which consisted of 1348 persons, this was not feasible. It is likely that consideration of the varying contamination of food and air
10
would still increase the range and distribution of exposure presented in Figs 1-3. To demonstrate the possible effect of variation on the intake, the averages, standard deviations and ranges of concentrations of lead and cadmium in some foods, tap water and air are given in Tables 1 and 2. CONCLUSIONS
The material collected in the FINMONICA survey proved to be useful for the study of the variation of lead and cadmium exposure and the effect of different factors on that exposure. The advantage of the approach of the FINMONICA study is that it provides (i) data on individuals' food consumption and smoking, (ii) food contamination data, i.e. files on the lead and cadmium content of food items and (iii) data on other factors, such as place of residence. Alternatively, an epidemiological study may not be advantageous if it is used to estimate total heavy metals exposure. The disadvantage of the present study is that the variation of the lead and cadmium content of food is not taken into account, as the calculation is based on food composition tables rather than on individual analyses. Also, exposure from urban air and drinking water can be described only by mean values, since locally representative analytical results are not available. Methodological problems in calculating intakes from food include invalidity of food composition data banks and difficulties in trace element analysis. Some methodological comparisons have been reported [28-30]. In all these studies the calculation method used seemed to overestimate the intake. The intake of lead and cadmium from foods is probably also overestimated in the present study. The main conclusion from these results is that the total exposure, i.e. the body burden from all sources - - food, air and drinking water, is to be considered in risk assessment as well as in establishing maximum tolerances of contaminants in food. In addition to lead and cadmium, PAH compounds, nitrates and nitrosoamines are examples of toxic compounds in food, which may also contaminate drinking water or air. The average exposure to lead and cadmium in Finland can be considered to be low when compared with the PTWI values. However, the present study shows that several factors increase the exposure of certain groups of the population. The upper extreme of the distribution curve of the total cadmium exposure (Fig. 3) is rather close to the PTWI value of cadmium, when the PTWI value is calculated as the absorbed amount. Also, certain other covariants of nutrition should be considered, since, for example, deficiency of calcium, iron and protein modifies the effect of lead, and copper and zinc deficiency increases the absorption of cadmium [31]. REFERENCES 1 2
WHO, Global Environmental Monitoring System, Guidelines for the study of dietary intakes of chemical contaminants, WHO, Offset Publication No. 87, Geneva, 1985. D.G. Lindsay, Estimation of the dietary intake of chemicals in food, Food Addit. Contam., 3 (1986) 71 88.
11 3 4
5
6 7
8 9 10 11
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18 19 20 21
22 23 24
K. Louekari, A. Scott and S. Salminen, Estimation of Food Additive Intakes, Food Additives, Marcel Dekker Inc., New York (in press). P. Weigert, I. Miiller, H. Klein and K.P. Zufelde, Arsen Blei, Cadmium and Quecksilber in und aur Lebensmitteln, ZEBS-Hefte 1184, Zentrale Erfassungs und Bewertungsstelle fiir Umweltchemikalien des Bundesgesundheitsamtes, Berlin, 1984. M. Fujita, K. Morikawa, H. Nakazawa, H. Matsushita, K. Tauabe, Y. Magara, Y. Fukushima, Y. Saitoh, T. Suzuki, T. Seki, Y. Mishima, T. Kawamura, H. Kigawa, Y. Sata, S. Karasawa, T. Nishimane, K. Ikebe and T. Yakushiji, Assessment of Total Human Exposure to Environmental Pollutants through Food, Water and Air, Annu. Rep. Inst. Public Health, 1986, 19 (1987) 1-24 (Abstract in English). A. Beloian, Use of food consumption model to estimate human contaminant intake, Environ. Monit. Assess., 2 (1981) 115-127. Global Environmental Monitoring System (GEMS), Food contamination monitoring programme, Summary of 1980-1981 Monitoring Data received from the Collaborating Centres, WHO, Geneva, 1983. National Academy of Sciences, The 1977 Survey of Industry on the Use of Food Additives, U.S. Department of Commerce, NTIS, PB-113418, 1979. L. Bander, K. Morgan and M. Zabik, Dietary lead intake of preschool children, Am. J. Public Health, 73 (1983) 789-794. K. Louekari and L. Salminen, Intake of heavy metals in Finland, West Germany and Japan, Food Addit. Contam, 3 (1986) 35~362. U. Ewers, A. Brockhaus, R. Dolgner, I. Freier, E. Jermann, R. Hahn, J. W. SchlipkSter and A. Bernard, Cadmiumbelastung und NierenfunktionsstSrungen, Staul~Reinhalt. Luft, 45 (1985) (Abstract in English). National Public Health Institute, Monitoring of trends and determinants of cardiovascular diseases in Finland (Part of a joint WHO study) the Monica project, Publications of the National Public Health Institute B 3/1986, 1986. P. Koivistoinen (Ed.), Mineral element composition of Finnish foods, Acta Agric. Scand., Suppl. 22 (1980) 1-171. L. Hiisvirta, J. Lehto, J. Kumpulainen, P. Koivistoinen and L. Pitk~inen, The effect of alkalization on the occurrence of metals in tap water. International workshop on water treatment and drinking water regulations, Vienna, June 1988 (preprint). J. Kumplainen, Low level of contaminants in Finnish foods and diets, Ann. Agric. Fenn., 27 (1988) 219-229. Helsingin kaupunginkanslia, ymp~iristSnsuorrelutoimisto, Leijuva p51y Helsingiss~i vuosina 1978-1984 (Suspended particles in the air of Helsinki 1978-1984), Helsingin Kaupungin Ymp~iristSnsuojelulautakunta, Julk., 2 (1986) 1-40 (in Finnish). Kuopion kaupunginkanslia, suunnitteluosasto/ympfiristSnsuojelutoimisto, Kuopion ilman laatu 1984--1986 (Air quality in Kuopio, 1984-1986), Vuosittaisjulkaisutja Erillistutkimukset, B3 (1987) 1 47 (in Finnish). J. Hirn and A. Salmi, The cadmium and selenium content of muscle, liver and kidney from cattle and swine, Fleischwirtschaft, 64 (1984) 464~465. H. Vornamo, Metallit ja asbesti yhdyskuntailmassa, Ymp~irist5 ja Terveys, 13 (1982) 18~185. A. AhlstrSm L. R~is/inen and K. Kuvaja, A method of data processing for food-consumption surveys, Ann. Acad. Sci. Fenn., Ser. A4, 194 (1972) 1-8. U. Uusitalo, P. Pietinen and U. Leino, Food and nutrient intake among adults in East and Southwest Finland - - a dietary survey of the Finmonica project in 1982, Publication of the National Public Health Institute B 1/1987, 1987. V. Riihim~ki, Cadmium, occurrence and effects, Work Environ. Health, 9 (1972) 91 101. D. Szadkowski, H. Schulze, K.-H. Schaller and G. Lehnert, Zur 5kologishen Bedeutung des Schwermetallgehaltes von Zigaretten, Arch. Hyg. Bacteriol., 1 (1969) 153. A. Lepp~inen and H. Liukkonen-Lilja, Analysis of tobacco smoke, Summary of studies during 1977 1989, Technical Research Centre of Finland, Research Report No. 86, Espoo, 1982.
12 25
P.-O. Ostrand and K. Rodahl, Textbook of Work Physiology, McGraw-Hill Book Company, New York, 3rd edn, 1986. 26 E.L. Eaton, D. Kalman, K. Garvey, M. Morgan and G.S. Omenn, Biological availability of lead in a paint aerosol, 2. Absorption, distribution and excretion of intratracheally instilled lead paint particles in the rat, Toxicol. Lett., 22 (1984) 307-313. 27 T. Moreau, J. Lellouch, B. Juguet, B. Festy, G. Orssaud and J.F. Claude, Blood cadmium levels in a general male population with special reference to smoking, Arch. Environ. Health, 38 (1983) 163-167. 28 T.J. Coomes, J.C. Sherlock and B. Walters, Studies in dietary intake and extreme food consumption, J. R. Soc. Health, 102 (1982) 119-123. 29 J. Kumpulainen, M. Mutanen, M. Paakki and J. Lehto, Validity of calculation method in estimating mineral element content of pooled total daily diet as tested by chemical analysis, Var FSda, Suppl. 1/87 (1987) 75 82. 30 K. Louekari, L. Jolkkonen and P. Varo, Exposure to cadmium from foods, estimated by analysis and calculation - - comparison of methods, Food Addit. Contam., 5 (1988) 111-117. 31 J.N. Hathcock, Nutrition: toxicology and pharmacology, Nutr. Rev., 34 (1976) 65-70.
1
VARIATION A N D MODIFYING FACTORS OF THE EXPOSURE TO LEAD AND CADMIUM B A S E D ON AN EPIDEMIOLOGICAL STUDY
K. LOUEKARI
Ministry of Agriculture and Forestry, Food Research Program, Viikki 22 A, SFo00710 Helsinki (Finland) U. UUSITALO and P. PIETINEN
National Public Health Institute, Department of Epidemiology, Mannerheiminte 166, SF-00280 Helsinki (Finland) (Received March 15th, 1988; accepted January 24th, 1989)
ABSTRACT Exposure to cadmium and lead was studied using a dietary survey. Data for 1348 individuals aged 25-64 years were collected using 3-day food records. In addition to the dietary intake of heavy metals, the effect of the following were also analyzed: smoking frequency, place of residence, occupation and age. Total cadmium and lead exposure was estimated by calculating intake from food plus that from inhalation, i.e. from urban air and smoking. Heavy smoking increased the cadmium exposure three-fold. The distribution curve of total cadmium exposure was bimodal due to the additional exposure caused by smoking. The distribution curve of the lead and cadmium exposure from food was also skewed, being mostly influenced by food intake. Contaminated urban air slightly increased the total exposure to lead. Occupation had a minor effect on the exposure to both metals. Housewives and retired persons were the least exposed groups. The distribution pattern and wide range of heavy metal exposure should be taken into account in risk assessment for contaminants in food. The additional exposure to cadmium and lead from smoking and from air and water should be considered.
INTRODUCTION
The intake of food contaminants is estimated in order to evaluate the safety of the food supply. A variety of methods are available for estimation of intake; many of them originate from dietary surveys and have recently been adopted in food toxicology. Comprehensive reviews on the methods have recently been p r e p a r e d [1-3]. I n s o m e c o u n t r i e s , t h e a v e r a g e i n t a k e o f l e a d a n d c a d m i u m is r e l a t i v e l y c l o s e to t h e p r o v i s i o n a l t o l e r a b l e w e e k l y i n t a k e s ( P T W I ) s u g g e s t e d b y t h e W o r l d H e a l t h O r g a n i s a t i o n (WHO). F o r e x a m p l e , i n t h e F e d e r a l R e p u b l i c of G e r m a n y , t h e e s t i m a t e of t h e i n t a k e o f l e a d a n d c a d m i u m is 40 a n d 70% of P T W I v a l u e s , r e s p e c t i v e l y [4]. H o w e v e r , t h e i n t a k e o f h e a v y m e t a l s , a n d a l s o t h a t of o t h e r c o n t a m i n a n t s of food, v a r i e s c o n s i d e r a b l y . V a r i a t i o n c a n b e d e s c r i b e d u s i n g t h e 90th p e r c e n t i l e o r t h e r a n g e o f i n t a k e . T h e s e d a t a a r e
0048-9697/89/$03.50
© 1989 Elsevier Science Publishers B.V.
included in some recent reports of intake studies, since they provide essential information for risk assessment [5-8]. Variation of intake of food contaminants is a result of different food consumption habits and varying types of environmental contamination [9-11]. Food consumption is dependent on several socio-economic and physiological variables: for example, age and occupation are determinants of energy requirement. In addition, other routes of exposure, especially respiratory intake, affects the total body burden. Smoking and urban air increase the total exposure to lead and cadmium and this should be considered when the significance of food contamination by these elements is assessed. How should the variation of total intake and the intake of groups at risk be monitored in order to regulate the maximum allowed levels of contaminants in food adequately ? There are relatively few publications on the variation of intake of food contaminants. In most cases, the mean intake and often also the 90th percentile is reported. Obviously there is a need to study: (i) the applicability of epidemiological data for estimation of the variation of heavy metal intake and the total exposure; (ii) the effect of independent factors (age, profession, smoking, area of residence) to the total exposure; (iii) the distribution pattern (based on individual data) of the exposure for the population. METHODS
Subjects The FINMONICA project conducted by the National Public Health Institute is part of a multicenter project coordinated by WHO. The 1982 FINMONICA risk factor survey on cardiovascular diseases was carried out on a random sample of persons aged 25-64 years in the provinces of North Carelia and Kuopio in eastern Finland and in Turku-Loimaa in south-western Finland. These study sites were selected because a large difference between the areas in the incidence of cardiovascular diseases has been observed. The total number of participants was 6523. The dietary survey consisted of a subsample: persons born between the 7th and 12th of each month were asked to keep food records at home. Of those eligible, 80% completed the food record and thus the final number of participants was 1348 persons (653 men and 695 women).
Food consumption data and intake of lead and cadmium through food In the first population survey of FINMONICA, risk factor data as well as dietary data were collected. The present analysis is based on this survey carried out in 1982 in eastern and south-western Finland. Data on food consumption was collected on the basis of a three day food record. Detailed information was obtained on the type and amount of food
TABLE 1 Concentration of lead in Finnish drinking water, some food items and air Sample
n
Ref.
( 0.5-14.2
863
14
2-10
48 30 48 5
15 15 15 13
Concentration Average _+ SD
Tap water
(pg1-1)
Wheat flour Potatoes Pork meat Cabbage
Ozgkg -1)
Urban air
~ g m -3)
0.6 11 + 1 11 _+ 2 13 + 3 10 0.3"
Range
< 0.1~0.95
300
16,17
In the middle-sized cities.
consumed by the subjects during three successive days. The participants of the survey received oral and written instructions and forms for keeping the food record. Completed records were checked and coded in the National Public Health Institute. Tables, especially compiled for FINMONICA, were used to convert household measures into grams [12]. The cadmium and lead content of foods used in calculations were obtained from a comprehensive mineral element study of Finnish foods, consisting of the analysis of 1948 samples [13]. The sampling covered mills, slaughterhouses, dairies and various types of retail outlet. Many samples consisted of 10-40 subsamples, which were collected to be representative of the possible seasonal and local variation of food composition. Some average concentrations and ranges of this study, as well as other studies, are given in Tables 1 and 2. Intake of lead and cadmium from foods was calculated using food composition data and computer programs developed in the Department of Nutrition, University of Helsinki [20]. Detailed results of the 1982
TABLE 2 Concentration of cadmium in Finnish drinking water, some food items and air Sample
Concentration Average + SD
Tap water
(/zg 1 l)
Wheat flour Potatoes Pork meat Cabbage
~ g k g -1)
Urban air
(/zgm 3)
0.05 40 48 _+ 10 3 5 1
n
Ref.
863
14
1-17 5-10
14 44 48 5
15 13 15 13
0.~9
120
19
Range < 0.5-0.66 30-50
FINMONICA dietary survey have been published [21]. The distributions of the lead and cadmium exposure and the total exposure have not been considered previously.
Intake from ambient air, smoking and drinking water There were two major routes of cadmium exposure in the survey population: through cigarette smoking and from food. The total amount of cadmium absorbed by subjects was calculated by assuming that 5% of the cadmium via food is absorbed and that 0.05 #g of cadmium is absorbed from one cigarette [22-24]. The absorbed amounts of cadmium via both routes were added to provide the total exposure. In addition to the lead intake from food, the urban population is exposed to lead-polluted air. Monthly averages of air-lead content were available only for Kuopio, but not for Turku, the other city participating in the study [17]. Based on these and other air quality monitoring data for moderately contaminated Finnish urban areas outside the study, it was approximated that the lead content of the air of the two middle-sized cities of the study area (Turku and Kuopio) is on average 0.3gg m -3 [16,17]. This contributes 5.4pg day -1 to the total lead exposure, using a respiratory volume of 18 m a day- 1. This estimate of respiratory volume is based on modifications of data in current textbooks [25] and consists of three periods of 8 h: 8 m 3 during non-physical work, 7 m 3 during leisure and 3 m 3 during sleep. The amounts of lead entering humans from food and air were added to provide the total exposure. Biological availability of lead is strongly dependent on the chemical form and particle size; there are no conclusive estimates about absorption [26]. Drinking w a t e r also contributes to exposure from heavy metals, which has been estimated to be 0.1~g day -1 for cadmium and 1.2ttg day 1 for lead in Finland. This is a minimal proportion of the total intake and it has been estimated t h a t only for 5% of waterworks does the drinking water contribute > 5% to the total intake of lead and cadmium [14]. It was not possible to calculate local intakes of lead and cadmium from drinking water, since the tap water study mentioned above was separate from the FINMONICA project and the sampling areas were different. Moreover, no geographical variation, which could be explained by quality of soil or local air pollution, has been found. The materials constituting the water pipes and distribution systems seem to be the origin of elevated heavy metal concentrations in tap water (Tables 1 and 2). This epidemiological study covers the inter-individual differences and differences between areas in food consumption and smoking, but not local data on the contamination of air and drinking water.
Modifying factors The factors affecting lead and cadmium intake selected from the risk factors
5 of the F I N M O N I C A s t u d y were smoking, age and o c c u p a t i o n . The s m o k i n g f a c t o r was classified as follows: Class 1 Non-smoking 2 Occasional smoking 3 Moderate smoking 4 Heavy smoking
C i g a r e t t e s per day 0 1-10 11-25 26-80
Age was also classified and i n t a k e s were estimated at 10-year intervals for b o t h sexes. O c c u p a t i o n was classified into the following categories: farmers, blue-collar workers, white-collar workers, students, housewives, retired and unemployed. Significance of differences b e t w e e n g r o u p s was tested by analysis of v a r i a n c e and D u n c a n ' s multiple r a n g e test. RESULTS AND DISCUSSION H e a v y s m o k i n g caused a three-fold exposure to c a d m i u m c o m p a r e d with the a v e r a g e n o n - s m o k e r (Table 3). A b o u t 5% of adult men smoked > 25 c i g a r e t t e s a day. In this g r o u p the a m o u n t of absorbed c a d m i u m was estimated to be 2.6 gg d a y - l ; the absorbed a m o u n t of c a d m i u m for the a v e r a g e n o n - s m o k e r was only 0.8 pg d a y - ' . Differences between the g r o u p s presented in Table 1 are s t a t i s t i c a l l y significant (p < 0.01). This is in a g r e e m e n t with the o b s e r v a t i o n t h a t the m e a n level of c a d m i u m in blood of c u r r e n t smokers is a p p r o x i m a t e l y four-fold the m e a n of n o n - s m o k e r s [27]. TABLE 3 Effect of smoking on the total exposure to cadmium, calculated as absorbed amount of cadmium. It was assumed that 5% of the cadmium via food is absorbed and that 0.05/~gof cadmium is absorbed from one cigarette Sex
Smoking cigarettes day- i
Total absorbed cadmium ~g day 1) Mean
SD
n
Men
0 (non-smoking) 1-10 (occasional) 11-25 (moderate) 26-80 (heavy) All
0,80 1.07 1.69 2.58 1.11
0.24 0.26 0.30 0.69 0.56
405 63 147 29 644
Women
0 (no smoking) 1 10 (occasional) 11-25 (moderate) 26-80 (heavy) All
0.64 0.94 1.48 2.33 0.74
0.18 0.25 0.25 0.28 0.32
566 69 52 3 690
All differences between groups are statistically significant (p < 0.001).
Urban air had a slight, but statistically significant, effect on the total lead exposure in this study. In the present study the mean lead exposure (59.4 pg day t) of urban people was only 3-4#g day 1 higher than the average lead exposure of rural people (56.1#g day-t). However, no accurate results of air lead analysis were available. The present results are based on the approximation that in relatively small cities ( ~ 75000 inhabitants) in the study areas the lead content of air is 0.3/~g m -3 [17]. Obviously in many urban areas in industrialized countries this concentration of lead in ambient air is exceeded and should be considered together with oral exposure when lead-induced risk is assessed. The distribution curve of lead and cadmium intake via food was skewed in the present study (Figs 1 and 2). This was due to a similar distribution pattern for food consumption among the participants of the study. High food consumption was more common than food consumption below nutritional requirements. This observation suggests that the average intake of food contaminants is not an adequate basis for risk assessment, since the intake of certain consumer groups is two or three times higher than the average intake. The distribution pattern of total absorbed cadmium (from food and smoking) was more skewed (Fig. 3) than the curve of cadmium intake from food. The curve was slightly bimodal. A small secondary peak at 1.5pg day -t (absorbed amount) represents moderate smokers, who are more abundant than occasional smokers in this study (Table 3). Age has a significant effect on the intake of lead and cadmium from food. Lead and cadmium intake in the oldest (60-64 years) age group was significant150 14-0 130 120
7 / / / / / / / / / / / / / / / / / /
110 1 O0 9O E
80
0"
70 6O 50 4O 30 2O 10
w / / / /
0
I
2
4
6
8
10
12
I4
16
18
Intake
Fig. 1. Distribution of cadmium intake from food.
l
l
20
l
l
]
22
(;Jg/d)
l
I
I
24
I
I
26
l
,777-
l
28
30
32
34
300 28O 260 240 220 // // // // // // // // // // // // // // // // // //
2OO 18Q c
16Q
g-
14-0 120 1QO 8O 6O 40 2O 0 0
15
25
// // //
/A //1 /A
// x ,, z/ //
/A //1 / f //
~ //
//
//
//
//
/ /
/ /
//
//
/ /
//
//
//
//
/ /
/ /
//
//
//
//
//
/ /
//
//
/ /
// //
//
/ /
/ /
//
//
//
//
//
//
//
//
/I /,;
// //
// / /
/
/
i
I
35
45
/
55
65
75
85
95
105
115
125
135
14-5 1 5 5
(pg/d)
Intake
Fig. 2. Distribution of lead intake from food.
220 200 180 160 140
c
120
,Y
100 80 60 40
0
_FI I
I
I
i
0.5
i
i
i
i
i
i
I Exposure
i
t
i
i
i
I .5 (absorbed
i
~
i
i
i
2 amount)
i
i
J
i
2.5
i
i
i
i
3
i
~ I I T ~ 3.5
)Jg/day
Fig. 3. Distribution of total cadmium exposure. Includes the intake from food and smoking.
8
TABLE 4 Lead and cadmium intake ~ g day -1) according to age group Sex
Age
Lead
Cadmium
n
Men
25 29 30-39 40-49 50-59 60-64 All
62 69 62 55 51 61
17 17 16 14 13 16
56 193 141 186 77 653
Women
25-29 30-39 4049 50-59 60-64 All
53 54 49 49 43 50
13 13 13 13 12 13
53 178 183 188 93 695
Statistically significant differences between groups (both sexes): Cadmium intake 60-64 vs 50-59 p < 0.01 60~4 vs others p < 0.001 25-29 vs 50-59 p < 0.01 30-39 vs 40-49 p < 0.01 30-39 vs 50-59 p < 0.001
Lead intake 60-64 vs 50-59 p < 0.01 60-64 vs others p < 0.001 30-39 vs 40-49 p < 0.001 30-39 vs 50-59 p < 0.001
l y l e s s ( p = 0.0001-0.0038) t h a n i n t h e o t h e r f o u r a g e g r o u p s ( T a b l e 4). L e a d i n t a k e o f t h e 30-39 y e a r s a g e g r o u p w a s s i g n i f i c a n t l y h i g h e r ( p < 0.001) t h a n the 40-49 and 50-59 year age groups. Cadmium intake of the 50-59 years age g r o u p w a s s i g n i f i c a n t l y s m a l l e r ( p = 0.001-0.0080) t h a n t h o s e o f t h e f i r s t t w o a g e g r o u p s (25-29 a n d 30-39). I n c o n t r a s t , t h e c a d m i u m i n t a k e p e r 1000 k c a l w a s e s t i m a t e d t o b e s i g n i f i c a n t ly s m a l l e r i n y o u n g e r t h a n i n e l d e r l y a g e g r o u p s . H o w e v e r , t h e r e w e r e n o s i g n i f i c a n t d i f f e r e n c e s b e t w e e n a g e g r o u p s i n t h e l e a d i n t a k e p e r 1000 k c a l . T h i s s u g g e s t s t h a t t h e a m o u n t o f f o o d c o n s u m e d is t h e m a j o r f a c t o r c o n t r i b u t i n g t o t h e d i f f e r e n c e s o b s e r v e d i n l e a d i n t a k e b e t w e e n a g e g r o u p s ( T a b l e 4). T h e s t a n d a r d d e v i a t i o n o f l e a d a n d c a d m i u m i n t a k e i n a g e g r o u p s is r a t h e r s m a l l , i.e. < 26 a n d 5 # g d a y -1, r e s p e c t i v e l y . I n a d d i t i o n t o a g e , t h e i n d i v i d u a l f o o d consumption habits, as well as varying demand of energy, causes variation of the intake of food contaminants. Occupational status also seems to affect the intake of lead and cadmium f r o m food. H o u s e w i v e s a n d r e t i r e d p e r s o n s h a d l o w e r c a d m i u m a n d l e a d i n t a k e c o m p a r e d w i t h o t h e r g r o u p s ( T a b l e 5). H o w e v e r , s i m i l a r d i f f e r e n c e s w e r e n o t o b s e r v e d w h e n c a d m i u m a n d l e a d i n t a k e p e r 1000 k c a l w e r e a n a l y z e d . T h i s suggests that age and sex partly explain the differences stated above. Whitec o l l a r w o r k e r s h a d a h i g h e r l e a d i n t a k e p e r 1000 k c a l t h a n f a r m e r s a n d b l u e c o l l a r w o r k e r s (p < 0.001). W h i t e - c o l l a r w o r k e r s , h o u s e w i v e s a n d r e t i r e d
TABLE 5 O c c u p a t i o n a l s t a t u s and i n t a k e of cadmium and lead from food Occupational status
1. F a r m e r s 2. Blue-collar workers 3. White-collar workers 4. S t u d e n t s 5. H o u s e w i v e s 6. Retired p e r s o n s 7. Unemployed p e r s o n s
Cadmium i n t a k e
Lead intake
Mean
SD
Mean
SD
15.1
5.0
58.0
24.1
212
15.0
5.1
58.4
24.4
302
13.9 16.8 12.5 12.4 14.7
4.2 6.3 3.8 3.4 4.5
55.8 68.2 45.7 48.7 52.2
21.8 26.4 19.8 21.3 21.2
528 9 99 155 18
Statistically significant differences b e t w e e n g r o u p s (both sexes): Cadmium lvs3p lvs5p lvs6p 2vs3p 2vs5p 2vs6p 3vs5p 3vs6p 4vs5p 4vs6p
intake < 0.001 < 0.001 < 0.001 < 0.01 < 0.001 < 0.001 < 0.01 < 0.001 < 0.01 < 0.(}1
Lead intake lvs5p < 0.001 lvs6p < 0.001 2 v s 5 p < 0.001 2 v s 6 p < 0.001 3 v s 5 p < 0.001 3 v s 6 p < 0.001 4vs5p < 0.01
persons had a significantly higher intake of cadmium per 1000 kcal than farmers and blue-collar workers. This suggests that greater demand for energy is provided by eating foods with low cadmium concentration, i.e. meat and dairy products. Students (n = 9) had the highest intake of lead and cadmium (72 and 17#g day 1, respectively), but the difference was statistically significant only when compared with housewives and retired persons (p < 0.01). However, the size of the group is too small for any definite conclusions regarding students. It should be noted that the lead and cadmium intake of individuals is calculated using average values of the lead and cadmium content of food items. However, heavy metal concentrations in food items vary due to varying deposition of pollutants, concentration of metals in fertilizers and soil conditions, although the most important point sources of emissions are far from the study areas. The composition of the food actually eaten is different for ali individuals. To take this into consideration would require determination of heavy metals in duplicate meal samples of every individual in the study. For the present study cohort, which consisted of 1348 persons, this was not feasible. It is likely that consideration of the varying contamination of food and air
10
would still increase the range and distribution of exposure presented in Figs 1-3. To demonstrate the possible effect of variation on the intake, the averages, standard deviations and ranges of concentrations of lead and cadmium in some foods, tap water and air are given in Tables 1 and 2. CONCLUSIONS
The material collected in the FINMONICA survey proved to be useful for the study of the variation of lead and cadmium exposure and the effect of different factors on that exposure. The advantage of the approach of the FINMONICA study is that it provides (i) data on individuals' food consumption and smoking, (ii) food contamination data, i.e. files on the lead and cadmium content of food items and (iii) data on other factors, such as place of residence. Alternatively, an epidemiological study may not be advantageous if it is used to estimate total heavy metals exposure. The disadvantage of the present study is that the variation of the lead and cadmium content of food is not taken into account, as the calculation is based on food composition tables rather than on individual analyses. Also, exposure from urban air and drinking water can be described only by mean values, since locally representative analytical results are not available. Methodological problems in calculating intakes from food include invalidity of food composition data banks and difficulties in trace element analysis. Some methodological comparisons have been reported [28-30]. In all these studies the calculation method used seemed to overestimate the intake. The intake of lead and cadmium from foods is probably also overestimated in the present study. The main conclusion from these results is that the total exposure, i.e. the body burden from all sources - - food, air and drinking water, is to be considered in risk assessment as well as in establishing maximum tolerances of contaminants in food. In addition to lead and cadmium, PAH compounds, nitrates and nitrosoamines are examples of toxic compounds in food, which may also contaminate drinking water or air. The average exposure to lead and cadmium in Finland can be considered to be low when compared with the PTWI values. However, the present study shows that several factors increase the exposure of certain groups of the population. The upper extreme of the distribution curve of the total cadmium exposure (Fig. 3) is rather close to the PTWI value of cadmium, when the PTWI value is calculated as the absorbed amount. Also, certain other covariants of nutrition should be considered, since, for example, deficiency of calcium, iron and protein modifies the effect of lead, and copper and zinc deficiency increases the absorption of cadmium [31]. REFERENCES 1 2
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