Recommended Rice Intake Levels Based on Average Daily Dose and Urinary Excretion of Cadmium in a Cadmium-Contaminated Area of Northwestern Thailand

Aroon La-Up1, Phongtape Wiwatanadate1, Sakda Pruenglampoo2, and Sureeporn Uthaikhup3

1Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand, 2Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand, 3Department of Physical Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand
Phongtape Wiwatanadate, Department of Community Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand, E-mail: pwiwatanadate@gmail.com
Received: April 20, 2017; Revised: June 7, 2017; Accepted: July 4, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

Keywords : Dose-response, Average daily cadmium dose, Urinary cadmium, Binary logistic regression
INTRODUCTION

Diet is the major source of cadmium exposure for the general non-smoking Thai population. Rice is the main dietary staple of the Thai people and, because of its ability to absorb cadmium, may be an important source of this metal. Rice is consumed in several meals daily, and therefore may allow the accumulation of cadmium in the body to the extent of impairing human health over a long period of time.

MATERIALS AND METHODS

This observational, retrospective, epidemiological cohort study was conducted in two areas, which were suitable for comparison because of differences in their environmental cadmium levels. In contaminated areas, soil cadmium levels may be as high as 284 mg/kg, 1800 times higher than levels in non-contaminated areas (14). The subjects for this study were people aged 18 or above, who had lived in one of the two areas for more than one year. The sample size was determined using StatCalc sample size and power calculations from the Epi-info 7 software program (AcaStat Software, Poinciana, FL, USA), and the samples were identified using a proportional stratified random sampling method, to ensure coverage of the populations of all villages in the areas. Samples from each village were identified by a drawing method to obtain subjects from the two different areas that were identical or similar in terms of gender and age variables.

This study was approved by the Research Ethics Committee, Faculty of Medicine, Chiang Mai University. The purpose of this investigation and the research procedures were explained to each subject before they signed the participation consent form.

### Measurement of cadmium in consumed rice

A one-spoonful sample of cooled, cooked rice was collected and placed in a transparent zip sachet with a label attached to its front showing the sample details. The samples were kept at room temperature and then sent to the Science and Technology Service Center, Faculty of Science, Chiang Mai University (STSC-CMU), to determine the cadmium content using the inductively coupled plasma-mass spectrometry (ICP-MS) method, which has been certified for quality by the Thai Industrial Standards Institute (TISI).

The average cadmium exposure from rice since birth, or moving into the area, until the day of sample collection was calculated using a formula adapted from the U.S. EPA (15) as follows:

$ADCD=C×IR×EF×EPBW×D$

Where ADCD is the average daily cadmium dose from rice consumption (ADCD: μg/kg body weight/day); C is cadmium concentration in rice (μg/kg); IR is rice intake (g/day); EF is exposure frequency (days/year); EP is exposure period (years); BW is average body weight (kg); and D is duration of exposure (days). The body weight average is calculated from the weight measured on the day of data collection and from medical records kept at Mea Sot General Hospital and the sub-district health promotion hospital, both of which serve the villages (Mae-Ku, Pra-That-Pha-Dang, Mae-Tao, Mae-Ka-Sa, Mae-Kued-Luang) in the research areas. IR data were collected using a semi-food frequency questionnaire (16), while EF, EP, and D were obtained by means of questionnaire interview.

### Measurements of U-Cd

Subjects’ second voided morning urine samples were collected. Specimen aliquots of 3 mL were frozen at −20°C until they could be tested in the laboratory. U-Cd concentration was analyzed using graphite furnace atomic absorption spectrometry (Varian Model AA280Z, Palo Alto, CA, USA) at the Mae Sot General Hospital laboratory, and the test results were quality-assured using Lyphocheck® (Bio-Rad, Gladesville, New South Wales, Australia).

### Statistical analysis

Results from the studied samples were expressed in terms of percentage, arithmetic mean, and standard deviation. Quantitative analysis was performed by transforming the data into logarithms to obtain geometric means. Then, a chi-square test was used to compare proportions between the two sample groups. Additionally, an ANOVA or Mann-Whitney U test was used for comparisons between means.

The prevalence of U-Cd was determined using ≥ 2 μg/g creatinine as the cut-off value. Statistical results from logistic regression using SPSS ver. 22 (IBM, Singapore) were used to evaluate the dose-response relationship between ADCD and U-Cd at each location, where the prevalence of U-Cd is a criterion variable and ADCD is an explanatory variable.

RESULTS

From a total of 567 observations, no statistically significant difference was found in terms of gender, age, and smoking status between the two groups of individuals, who were divided into those living in the contaminated and non-contaminated areas (Table 1).

The group geometric means of U-Cd concentration were 1.32 and 0.47 μg/g creatinine for those from the contaminated and non-contaminated areas, respectively. A statistically significant difference existed between the two groups, indicating that those living in the contaminated area, even when subdivided on the basis of gender, age, and smoking status, had higher U-Cd concentrations than their counterparts. Considering gender, although both males and females in the contaminated area had significantly higher U-Cd concentrations, females in both areas appeared to have higher levels than their male counterparts. Age was found to be positively associated with U-Cd concentration only in the contaminated area (p < 0.05) (Table 2).

As shown in Table 3, the median value of average daily cadmium dose from rice is 0.06 μg/kg bw/day. There is no difference with respect to gender and age variables, but a difference exists between the median value in the contaminated area (0.29 μg/kg bw/day) and that in the non-contaminated area (0.00 μg/kg bw/day). The variety of rice was also a significant factor, with the median value for RD6 rice consumers (0.28 μg/kg bw/day) being higher than that for KDML-105 consumers (0.04 μg/kg bw/day).

The prevalence of U-Cd ≥ 2 μg/g creatinine (Table 4) differs at a statistically significant level, with 101 people (35.1%) in the contaminated area and 20 people (7.2%) in the non-contaminated area having levels of this magnitude.

The investigation of the dose-response relationship between ADCD from rice and U-Cd based on the data from all studied subjects shows ADCD = 0.5 μg/kg bw/day to be at a statistically significant level, with an odds ratio (OR) = 1.71, 95% CI = 1.02~2.87. The OR increases when ADCD increases, after adjusting for gender, age, smoking status, and location. When location is taken into account, the findings reveal that this relationship exists at an ADCD of 0.7 μg/kg bw/day with an OR = 1.84, 95% CI = 1.06~3.19 in the contaminated area; whereas in the non-contaminated area, a statistical relationship cannot be established, due to the absence of ADCD at ≥ 0.7 μg/kg bw/day (Table 5).

Table 6 shows the estimated consumption of rice with varying degrees of cadmium contamination, but not exceeding 400 μg/kg as recommended by CODEX, categorized by gender, for different age groups, as well as overall results for the different age groups. The estimation was made by applying the formula for calculating ADCD. Since, in this case, the highest level of ADCD found to have no relationship with U-Cd is 0.6 μg/kg bw/day, this figure was used for back-calculation or inference of rice intake, taking into account the average body weight, for different categories of gender, age, and cadmium concentration in rice. To summarize the findings, the population in general should consume locally grown rice at a rate of no more than 246.8 g/kg per day (in the case where cadmium concentration of the rice is not known), but they can refer to the information in Table 6 for a recommended rate of rice intake if the cadmium concentration in the rice is known. However, rice containing more than 400 μg/kg cadmium should not be consumed.

DISCUSSION

This study attempted to gain an insight into the relationship between ADCD from rice and U-Cd. It is imperative to prevent the adverse effects of excessive cadmium intake on human health, and U-Cd represents a good indicator of its physiological impact. Although there have been several studies addressing a dose-response relationship between dietary cadmium intake and rice consumption (1719), the findings are quite diverse, leading to differing conclusions across the different locations and regions of the studies.

The study showed a positive relationship between ADCD and the prevalence of U-Cd ≥ 2 μg/g creatinine, but only in the contaminated area. We also found that ADCD = 0.6 μg/kg bw/day is the highest level at which no statistically significant relationship between ADCD and U-Cd exists. This is in contrast to a previous study undertaken in the same geographic area, with the same demographic coverage, showing that daily intake of 2.9~11.7 μg/kg bw/day had negative implications for public health (14). However, our results are in agreement with what was suggested at the 61st JECFA 2003, that a level of 0.4~0.6 μg/kg bw/day has implications for public health (23).

In this study, recommended daily rice intake was estimated on the basis of gender, age, and cadmium concentration in rice, because rice intake was hypothesized to vary significantly across groups and sub-groups. The findings suggest that rice with lower cadmium content could be consumed in larger quantities each day and vice versa. The population living in the contaminated area should be referred to this information to encourage them to restrict their daily rice intake in accordance with the known level of cadmium in the rice they grow and consume. In the absence of more precise knowledge, those in the contaminated area are advised to consume no more than 264.8 g/day of locally grown rice. Any rice known to have a cadmium concentration greater than 400 μg/kg should not be consumed at all according to CODEX (23). Although rice is the main source of cadmium exposure for people in contaminated areas, they might also ingest cadmium from other edible cadmium-absorbing crops that were not surveyed in the study.

This present study faced some limitations due to ethical concerns and operational practicality. The ADCD was estimated using average body weight, obtained from measurements at the time of the investigation and from medical records only, as weight records were not available from elsewhere. School records would have been particularly useful when the study participants were aged 18 years or older. In addition, the ADCD estimated only from rice consumption might not accurately reflect the true ADCD, as information regarding rice intake in the past may be associated with recall bias.

ACKNOWLEDGMENTS

This study was supported by funds from the Faculty of Medicine, Chiang Mai University and National Research Council of Thailand (NRCT).

ABBREVIATIONS
TABLES

### Table 1

Demographic characteristics of study participants

Group Contaminatedn = 288 Non-contaminatedn = 279 Totaln = 567 p-valuea
Sex Male 145 (50.3) 132 (47.3) 277 (48.9) 0.470
Female 143 (49.7) 147 (52.7) 290 (51.1)
Age < 25 57 (19.8) 52 (18.6) 109 (19.2) 0.991
25~34 56 (19.4) 52 (18.6) 108 (19.0)
35~44 59 (20.5) 58 (20.8) 117 (20.6)
45~54 57 (19.8) 59 (21.1) 116 (20.5)
55 + 59 (20.5) 58 (20.8) 117 (20.6)
Smoking Current 70 (24.3) 75 (26.9) 145 (25.6) 0.319
Ex-smoker 23 (8.0) 14 (5.0) 37 (6.5)
Never 195 (67.7) 190 (68.1) 385 (67.9)

### a

Result of chi-square test.

### Table 2

Mean concentration of cadmium in urine (μg/g creatinine) by demographic characteristics

Characteristics Group  Contaminated   Non-contaminated
GMa GSDb GMa GSDb
Sex Male 1.10 3.14 0.36 2.30
Female 1.59 2.43 0.60 2.34
p-valuec 0.003 < 0.01
Age < 25 0.60d 2.69 0.41 2.69
25~34 0.98e 2.29 0.55 3.45
35~44 1.51f 2.75 0.47 2.95
45~54 1.91g 2.57 0.41 2.57
≥ 55 2.24h 2.40 0.52 2.13
p-valuec 0.006 0.235
Smoking Current 1.10 2.69 0.46 2.45
Ex-smoker  1.82 2.57 0.33 2.57
Never 1.35 2.88 0.49 2.40
p-valuec 0.096 0.250
Total 1.32 2.83 0.47 2.41
p-valuec < 0.01

Geometric mean.

### b

Geometric standard deviation.

### c

Result of ANOVA followed by LSD test for multiple comparisons among group.

### d

Significant difference VS 25–34, 35–44, 45–54, and 55 or greater at p<0.05.

### e

Significant difference VS < 25, 35–44, 45–54, and 55 or greater at p<0.05.

### f

Significant difference VS < 25, 25–43, and 55 or greater at p<0.05.

### g

Significant difference VS < 25 and 25–34 at p<0.05.

### h

Significant difference VS < 25, 25–34, and 35–44 at p<0.05.

### Table 3

Rice consumption and average daily cadmium intake by demographic and rice group

Group Rice consumption (g/day)a Average daily cadmium dose (μg/kg bw/day)a
Sex Male 431.26 ± 204.91 0.52 ± 1.43a (0.05)b
Female 319.28 ± 313.71 0.36 ± 0.79a (0.06)b
p-value < 0.01c 0.402f
Age < 25 345.64 ± 173.29d 0.31 ± 0.73a (0.06)b
25~34 343.75 ± 168.66d 0.59 ± 1.68a (0.07)b
35~44 366.67 ± 213.99d 0.26 ± 0.67a (0.04)b
45~54 450.67 ± 469.16e 0.59 ± 1.29a (0.08)b
≥ 55 359.62 ± 185.61d 0.44 ± 1.06a (0.04)b
p-value 0.016c 0.080g
Location Contaminated 325.42 ± 151.17 0.83 ± 1.51a (0.29)b
Non-contaminated 424.13 ± 341.04 0.03 ± 0.07a (0.00)b
p-value < 0.01c < 0.01f
Rice KDML-105 388.63 ± 298.43 0.24 ± 0.59a (0.04)b
RD6 327.15 ± 150.45 1.10 ± 1.98a (0.28)b
p-value 0.002c < 0.01f
Total 373.99 ± 271.78 0.44 ± 1.15a (0.06)b

### a

Arithmetric mean ± standard deviation.

Median.

### c

Result of ANOVA followed by LSD test for multiple comparisons among group.

### d

Significant difference VS 45–54 at p<0.05.

### e

Significant difference VS < 25, 25–34, 35–44, and 55 or greater at p<0.05.

### f

Result of Mann-Whitney U test.

### g

Result of Kruskal-Wallis test.

### Table 4

Prevalence of U-Cd by location

U-Cd  Contaminated   Non-contaminated  p-value
n = 288 n = 279
< 2 μg/g creatinine  187 (64.9) 259 (92.8) < 0.01
≥ 2 μg/g creatinine 101 (35.1) 20 (7.2)

Result of chi-square test.

### Table 5

Logistic regression analysis of the dose-response relationship between average daily cadmium dose (ADCD) and urinary cadmium (U-Cd) cut-off point at 2 μg/g creatinine

0.1 0.86 0.5~1.5 0.598 0.5 0.1~4.3 0.052 0.9 0.5~1.5 0.868
0.2 0.96 0.6~1.6 0.870 0 0 0.999 1.0 0.6~1.6 0.924
0.3 1.19 0.7~2.0 0.511 0 0 0.999 1.2 0.7~2.0 0.447
0.4 1.31 0.8~2.2 0.313 0 0 0.999 1.4 0.8~2.2 0.249
0.5 1.68 0.9~2.9 0.059 0 0 0.999 1.7 1.1~2.9 0.042
0.6 1.71 1.0~2.9 0.052 0 0 0.999 1.7 1.1~2.9 0.044
0.7 1.84 1.1~3.2 0.032 - - - 1.8 1.1~3.1 0.025
0.8 1.89 1.1~3.3 0.027 - - - 1.9 1.1~3.3 0.020
0.9 2.26 1.3~4.0 0.005 - - - 2.3 1.3~4.0 0.004
1.0 2.22 1.2~4.1 0.010 - - - 2.2 1.2~4.0 0.007

### a

Odds ratio adjusted for sex, age, and smoking.

### b

Odds ratio adjusted for sex, age, smoking, and location.

### Table 6

Estimated rice intake by sex, age, and cadmium concentration in rice when ADCD = 0.6 μg/kg bw/day

Estimated rice intake (g/day)
Sex Age < 49 50~99 100~149 150~199 200~249 250~299 300~299 350~399 0.141a
Male 18~24 740.8 366.7 243.6 182.4 145.8 121.4 104.0 91.0 257.4
25~34 775.1 383.6 254.9 190.9 152.5 127.0 108.8 95.2 269.4
35~44 786.1 389.1 258.5 193.6 154.7 128.8 110.4 96.5 273.2
45~54 759.2 375.8 249.7 186.9 149.4 124.4 106.6 93.2 263.8
55 + 710.2 351.5 233.6 174.9 139.8 116.4 99.7 87.2 246.8
Female 18~24 619.6 306.7 203.8 152.6 121.9 101.5 87.0 76.1 215.3
25~34 680.8 337.0 223.9 167.6 134.0 111.6 95.6 83.6 236.6
35~44 645.3 319.4 212.2 158.9 127.0 105.8 90.6 79.2 224.3
45~54 699.2 346.1 229.9 172.2 137.6 114.6 98.2 85.9 243.0
55 + 679.6 336.4 223.5 167.3 133.7 111.4 95.4 83.5 236.2
Overall 18~24 655.5 324.5 215.6 161.4 129.0 107.4 92.0 80.5 227.8
25~34 742.3 367.4 244.1 182.8 146.1 121.7 104.2 91.2 258.0
3~44 734.0 363.3 241.4 180.7 144.4 120.3 103.1 90.1 255.1
45~54 747.4 369.9 245.8 184.0 147.1 122.5 104.9 91.8 259.7
55 + 704.2 348.5 231.6 173.4 138.6 115.4 98.9 86.5 244.7
Total average 710.2 351.5 233.6 174.9 139.8 116.4 99.7 87.2 246.8

### a

Average cadmium intake from rice grown in a contaminated area.

References
1. Vacchi-Suzzi, C, Kruse, D, Harrington, J, Levine, K, and Meliker, JR (2016). Is urinary cadmium a biomarker of long-term exposure in humans? A review. Curr Environ Health Rep. 3, 450-458.
2. Agency for Toxic Substances and Disease Registry (2008). Toxicological profile for cadmium. Atlanta, Georgia: U.S. Department Of Health And Human Services Public Health Service
3. Ilmiawati, C, Yoshida, T, Itoh, T, Nakagi, Y, Saijo, Y, Sugioka, Y, Sakamoto, M, Ikegami, A, Ogawa, M, and Kayama, F (2015). Biomonitoring of mercury, cadmium, and lead exposure in Japanese children: a cross-sectional study. Environ Health Prev Med. 20, 18-27.
4. Järup, L, and Akesson, A (2009). Current status of cadmium as an environmental health problem. Toxicol Appl Pharmacol. 238, 201-208.
5. Ke, S, Cheng, X-Y, Zhang, J-Y, Jia, W-J, Li, H, Luo, H-F, Ge, P-H, Liu, Z-M, Wang, H-M, He, J-S, and Chen, ZN (2015). Estimation of the benchmark dose of urinary cadmium as the reference level for renal dysfunction: a large sample study in five cadmium polluted areas in China. BMC Public Health. 15, 656.
6. Weaver, VM, Kim, N-S, Lee, B-K, Parsons, PJ, Spector, J, Fadrowski, J, Jaar, BG, Steuerwald, AJ, Todd, AC, Simon, D, and Schwartz, BS (2011). Differences in urine cadmium associations with kidney outcomes based on serum creatinine and cystatin C. Environ Res. 111, 1236-1242.
7. Egan, SK, Bolger, PM, and Carrington, CD (2007). Update of US FDA’s Total Diet Study food list and diets. J Expo Sci Environ Epidemiol. 17, 573-582.
8. Kido, T, Sunaga, K, Nishijo, M, Nakagawa, H, Kobayashi, E, and Nogawa, K (2004). The relation of individual cadmium concentration in urine with total cadmium intake in Kakehashi River basin, Japan. Toxicol Lett. 152, 57-61.
9. Kobayashi, E, Okubo, Y, Suwazono, Y, Kido, T, and Nogawa, K (2002). Dose-response relationship between total cadmium intake calculated from the cadmium concentration in rice collected from each household of farmers and renal dysfunction in inhabitants of the Jinzu River basin, Japan. J Appl Toxicol. 22, 431-436.
10. Llobet, J, Falco, G, Casas, C, Teixido, A, and Domingo, J (2003). Concentrations of arsenic, cadmium, mercury, and lead in common foods and estimated daily intake by children, adolescents, adults, and seniors of Catalonia, Spain. J Agric Food Chem. 51, 838-842.
11. Munoz, O, Bastias, JM, Araya, M, Morales, A, Orellana, C, Rebolledo, R, and Velez, D (2005). Estimation of the dietary intake of cadmium, lead, mercury, and arsenic by the population of Santiago (Chile) using a Total Diet Study. Food Chem Toxicol. 43, 1647-1655.
12. Chunhabundit, R (2016). cadmium exposure and potential health risk from foods in contaminated area, Thailand. Toxicol Res. 32, 65-72.
13. Swaddiwudhipong, W, Nguntra, P, Kaewnate, Y, Mahasakpan, P, Limpatanachote, P, Aunjai, T, Jeekeeree, W, Punta, B, Funkhiew, T, and Phopueng, I (2015). Human health effects from cadmium exposure: comparison between persons living in cadmium-contaminated and non-contaminated areas in Northwestern Thailand. Southeast Asian J Trop Med Public Health. 46, 133-142.
14. Simmons, RW, Pongsakul, P, Saiyasitpanich, D, and Klinphoklap, S (2005). Elevated levels of cadmium and zinc in paddy soils and elevated levels of cadmium in rice grain downstream of a zinc mineralized area in Thailand: implications for public health. Environ Geochem Health. 27, 501-511.
15. U.S. Environmental Protection Agency (1992). Guidelines for Exposure Assessment
16. Guest, C (1992). Design concepts in nutritional epidemiology. J Epidemiol Community Health. 46, 317.
17. Kido, T, and Nogawa, K (1993). Dose-response relationship between total cadmium intake and β2-microglobulinuria using logistic regression analysis. Toxicol Lett. 69, 113-120.
18. Kobayashi, E, Okubo, Y, Suwazono, Y, Kido, T, Nishijo, M, Nakagawa, H, and Nogawa, K (2002). Association between total cadmium intake calculated from the cadmium concentration in household rice and mortality among inhabitants of the cadmium-polluted Jinzu River basin of Japan. Toxicol Lett. 129, 85-91.
19. Ogawa, T, Kobayashi, E, Okubo, Y, Suwazono, Y, Kido, T, and Nogawa, K (2004). Relationship among prevalence of patients with Itai-itai disease, prevalence of abnormal urinary findings, and cadmium concentrations in rice of individual hamlets in the Jinzu River basin, Toyama prefecture of Japan. Int J Environ Health Res. 14, 243-252.
20. Satarug, S, and Moore, MR (2004). Adverse health effects of chronic exposure to low-level cadmium in foodstuffs and cigarette smoke. Environ Health Perspect. 112, 1099-1103.
21. Titapiwatanakun, B (2012). The Rice Situation In Thailand. Technical Assistance Consultant’s Report, TA-REG, 74595
22. Uraguchi, S, and Fujiwara, T (2012). Cadmium transport and tolerance in rice: perspectives for reducing grain cadmium accumulation. Rice (N Y). 5, 5.
23. Codex Alimentarius Commission 2011. ., Report of the 35th session of the Codex Committee on Food Additives and Contaminants, Fifth session, The Hague, The Netherlands.