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1 From the Departments of Internal Medicine (J-YG and H-CC) and Biochemistry (L-YC), Kaohs iung Medical University, Kaohsiung, Taiwan
2 The Nutrition and Health Survey in Taiwan was sponsored by the Department of Health in Taiwan (DOH FN8202, DOH-83-FS-41, DOH-84-FS-11, DOH-85-FS-11, DOH-86-FS-11) and carried out by W-H Pan (Institute of Biomedical Sciences, Academia Sinica) and P-C Huang (Department of Biochemistry, National Taiwan University). The views expressed herein are solely those of the authors. 3 Supported by grant no. DOH93-TD-D-113-021(2) from the Department of Health, Taiwan, ROC. 4 Address reprint requests to H-C Chen, Department of Internal Medicine, Kaohsiung Medical University, 100 Zihyou 1st Road, Kaohsiung, Taiwan 807, ROC. E-mail: jiyugu{at}kmu.edu.tw.
ABSTRACT
Background: Betel-quid use has been associated with obesity and hyperglycemia in previous studies.
Objective: The aim was to test whether betel-quid use contributes to the metabolic syndrome, as defined by the National Cholesterol Education Program Adult Treatment Panel III.
Design: Associations between betel-quid use and the metabolic syndrome, obesity, hypertriacylglycerolemia, low HDL cholesterol, hyperglycemia, and high blood pressure after adjustment for sex, age, smoking, alcohol drinking, physical activity, and dietary intakes were studied in nonpregnant adults aged 20–64 y (n = 1986) from the Nutrition and Health Survey in Taiwan (1993–1996).
Results: The prevalence of the metabolic syndrome was not significantly different between the men and women (10.1% compared with 9.7%), whereas the prevalence of betel-quid use was higher in the men than in the women (31% compared with 2.3%; P < 0.001). The daily rate of betel-quid use was associated with the metabolic syndrome [odds ratio (OR) associated with a betel-quid consumption rate of 10 times/d: 1.31; 95% CI: 1.12, 1.55; P = 0.003], abdominal obesity (OR: 1.42; 95% CI: 1.2, 1.7; P = 0.001), hypertriacylglycerolemia (OR: 1.33; 95% CI: 1.02, 1.73; P = 0.037), and high blood pressure (OR: 1.2; 95% CI: 1.01, 1.4; P = 0.04). However, the daily rate of betel-quid use was not associated with low HDL cholesterol or hyperglycemia.
Conclusion: The daily rate of betel-quid use is independently and positively associated with the metabolic syndrome in adults.
Key Words: Betel quid • metabolic syndrome • hyperglycemia • hypertension • obesity • hyperlipidemia
INTRODUCTION
Betel-quid use, the fourth most addictive habit in the world after nicotine, ethanol, and caffeine use, occurs in 10% of the world population, including that of Taiwan. Betel quid (Areca catechu) is usually chewed in combination with Piper betle leaf and lime, and the most abundant arecal alkaloid found in betel quids is arecoline, a parasympathomimetic agent that lowers blood pressure (BP) (1, 2). However, other arecal compounds are sympathomimetic substances that increase BP (3), and hypertension is part of the National Cholesterol Education Program Adult Treatment Panel III definition of the metabolic syndrome (4, 5).
Betel-quid use is associated with an increased risk of oral cancer, liver cirrhosis, and hepatocellular carcinoma (1, 2, 6, 7). Arecal nitrosamines have also been identified as carcinogenens (8). Moreover, studies conducted in humans (8, 9) and mice (10) found that betel-quid use was associated with abdominal obesity and hyperglycemia, 2 components of the metabolic syndrome. Thus, it is of interest to determine whether associations between betel-quid use and the metabolic syndrome exist. Therefore, data from the stratified multistage probability sampled Nutrition and Health Survey in Taiwan (NAHSIT, 1993–1996) (11) was used to address 2 questions. First, is betel-quid use independently associated with the metabolic syndrome? Second, is betel-quid use independently associated with all 5 components used to define the metabolic syndrome?
SUBJECTS AND METHODS
Study population
The Taiwanese population was 21 million in 1993-1996. The design and operation of NAHSIT was described elsewhere (12). Briefly, Taiwan was stratified into 7 strata, and 3 townships in each stratum were selected with the selection probability proportional to the population size of the townships. A total of 9961 persons aged 4–96 y were sampled (sampling rate: 0.047%). All NAHSIT enrollees signed the informed consent.
The present study was approved by the Kaohsiung Medical University ethics committee. Because 24-h dietary recall questionnaires were only administered to participants aged 13–64 y, the target population was adults aged 20–64 y. Thus, inclusion criteria were the following: nonpregnant adults aged 20–64 y (n = 3910). Exclusion criteria were the following: not receiving physical examination or phlebotomy (n = 1454), fasting <8 h or hemolyzed blood (n = 250), missing personal history (diabetes mellitus [DM], hypertension, smoking, alcohol drinking, betel-quid use, or physical activity; n = 115), missing dietary intake data (n = 133), or missing concentrations of blood glucose, plasma triacylglycerol, or HDL cholesterol (n = 205). Note that some NAHSIT participants met more than one exclusion criteria. Thus, data from 1986 persons were included in the study.
Interview
A household interview and physical examination were completed by technicians who received a 1-wk training course (12). Dietary intakes for those aged 20–64 y were estimated from 24-h dietary recalls and food-frequency questionnaires. The 24-h dietary recall (13, 14) included a recall of foods consumed within the 24 h before administering the 24-h dietary recall questionnaires. Nutrient intakes were calculated from each food item based on the Nutrient Composition Data Bank for Foods of Taiwan Area (15). The food-frequency questionnaire (16, 17) estimated the frequency of intake of 36 food items for 1 mo. The 24-h dietary recall and food-frequency questionnaire were validated by 2 previous studies with the use of an external dataset. These adults were interviewed every 3 mo at which time they were given a food-frequency questionnaire and asked to record their diets for the next 5 d. The 5 d included 3 weekdays and 2 weekend days. Data from 49 men and 20 women who had 2 or 3 interviews and 5-d dietary records within 6 mo were used (18, 19).
The question asked to ascertain betel-quid use was "how often do you chew betel quid (per day or per week)?" From the 368 betel-quid users, 216 reported use in times/d. The other 152 reported use in times/wk, which was converted to times/d. The frequency of betel-quid use was asked again in a different part of the interview to ensure accuracy. Note that the duration of betel-quid use was not asked. The questions to ascertain smoking status were the following: "are you currently smoking?", "at what age did you start smoking?", and "on average, how many packs do you smoke each day?" Smoking was then converted to pack-years. The questions to ascertain alcohol consumption were the following: "are you currently drinking alcohol?", "at what age did you start to drink alcohol?", and "on average, how often do you drink?" Alcohol consumption was then converted to drink-years. The question asked to ascertain the presence of DM was, "have you been diagnosed as having DM (also called ‘a disease with sugar in urine’ in lay terms) by a physician?" The question asked to ascertain for the presence of hypertension was, "have you been diagnosed as having hypertension (also called "high blood pressure" in lay terms) by a physician?"
Physical activity was assessed by the frequency of activity per week within 1 mo; activities included biking, ball games, gymnastics or boxing, swimming, dancing, mountain climbing, jogging, walking, gardening, housework, moving or loading objects, and mechanical assembling (20). Note that because physical activity was a composite score of several different physical activities, we classified physical activity as into 5 categories (0, 3, >3 and 7, >7 and 9, or >9 times/wk).
Body weight was measured to the nearest 0.1 kg with the use of a weighing scale while the participants wore light clothing (20). The scale was calibrated with a 20-kg counterweight before each measurement. Body height was measured to the nearest 0.1 cm with the use of a wall-glued metal measuring tape and an acute-angled head piece while the participants stood against a plumb-checked vertical wall and wore no shoes. Body mass index was calculated as weight (in kg)/height2 (in m). Waist circumferences were measured horizontally with a soft measuring tape at the level of the natural waist, which was identified as the level at the hollow molding of the trunk when the participants bent their trunks laterally (21). The participants were told to avoid smoking for 30 min before measuring BP, which was measured with the use of mercury sphygmomanometers after the participants had rested for 5 min in a supine position (22). Systolic BP (SBP) and diastolic BP (DBP) were recorded as the first and fifth phase of Korotkoff sound, respectively. Two BP measurements were made 30 s apart. If the 2 measurements differed by >10 mm Hg, a third measurement was made and the 2 closest BPs were averaged. The weighing scale, measuring tapes, and mercury sphygmomanometer were standardized by Bureau of Standards, Metrology, and Inspection–authorized agencies at the start of the study and at 6-mo intervals.
The metabolic syndrome was defined by abnormalities in 3 of the following criteria, which were modified from the National Cholesterol Education Program Adult Treatment Panel III criteria (4, 5): 1) abdominal obesity, defined as a waist circumference >90 cm for men and >80 cm for women (23, 24); 2) hypertriacylglycerolemia, defined as triacylglycerol concentrations 150 mg/dL; 3) low HDL-cholesterol concentrations, defined as an HDL-cholesterol concentration <40 mg/dL in men and <50 mg/dL in women; 4) hyperglycemia, defined as a fasting whole-blood glucose concentration 100 mg/dL (5.6 mmol/L) or DM [ie, fasting blood glucose 110 mg/dL (6.1 mmol/L), physician-diagnosed DM, or treated DM) (25); and 5) high BP, defined as SBP 130 mm Hg, DBP 85 mm Hg, or physician-diagnosed or treated hypertension. Note that the National Cholesterol Education Program Adult Treatment Panel III was ambiguous about treated hypertensive or diabetic patients who may have normal blood pressure or fasting blood glucose concentrations. Therefore, we adopted the above definitions of high blood pressure and hyperglycemia as defined by the International Diabetes Federation and used by previous studies (23, 24).
Analytic procedures
Fasting (8 h) morning blood samples were drawn and centrifuged at 1000 x g for 15 min at 4 °C on site. Venous whole-blood glucose was measured immediately by the glucose oxidase method with a glucose analyzer (model 23A; YSI, Yellow Springs, OH) in blood that was collected into sodium fluoride tubes (21, 22). Serum was stored in a single batch at –70 °C until analyzed within 1 mo for triacylglycerol and HDL cholesterol with the use of a Hitachi 747 autoanalyzer (Hitachi, Tokyo, Japan) (26).
Statistical analysis
The statistical package STATA version 8.2 (Stata Corp, College Station, TX) was used. Data were expressed as means (±SEMs). Triacylglycerol, HDL cholesterol, and fasting blood glucose were log-transformed before analyses to normalize the distribution. Statistical significance was defined as a P value of < 0.05.
The weighted "svy (svyreg: linear regression; svylogit: logistic regression)" or "robust" command was used to account for the complex survey design in NAHSIT. Differences between continuous variables and categorical variables were tested with unpaired t tests and chi-square tests, respectively. The effect of betel-quid use was examined in multiple linear or logistic regression analyses after adjustment for sex, age, smoking, alcohol drinking, dietary intakes, and physical activity. The above 2 statistical analyses were used to test for the effects of betel-quid use as a continuous or categorical variable.
An overall test for the effect of betel-quid use was performed with the F test, whereas linear trend tests for the effect of betel-quid use category (an ordinal independent variable) were performed by using orthogonal polynomial contrasts (with computer-generated contrast coefficients) (27) in multiple linear or logistic regression analyses. We also tested for the interaction of sex or age with betel-quid use in multiple linear regression and logistic regression analyses.
Note that the orthogonal polynomial contrast is a technique used for multiple comparisons (28). A contrast is a linear combination of 2 or more means with coefficients that sum to zero. Two contrasts are orthogonal (nonredundant and independent) if the sum of the products of corresponding coefficients (ie, coefficients for the same means) adds to zero. For J groups, we can only construct J-1 orthogonal contrasts. Trend analysis is performed when the category has a natural order. In polynomial regression, the model of the sample mean consists of coefficient terms: linear, quadratic, cubic, etc. A polynomial contrast is a set of contrasts evaluating trends: linear, quadratic, cubic, etc. Two polynomial contrasts are orthogonal if the sum of the products of corresponding coefficients adds to zero. Thus, we have 2 contrasts (evaluating linear and quadratic trends), which are orthogonal, for the 3 betel-quid use categories.
RESULTS
Demographic characteristics of NAHSIT enrollees who did or did not participate
The participation rate was 51% (1986 of 3910). A lower percentage of men was observed in the participants subgroup than in the nonparticipants subgroup (47% compared with 56%, P = 0.003). Thus, data were analyzed separately for men and women. Moreover, the participants were older than were the nonparticipants in both the male group [
Prevalence of betel-quid use in NAHSIT participants
The overall prevalence of betel-quid use was 15.9%, which was higher in the 920 men than in the 1066 women (31% compared with 2.3%, respectively; P < 0.001). In betel-quid users, the median frequency of betel-quid use was 3.5 times/d (first quartile: 0.33 times/d; third quartile: 10 times/d). Thus, the daily rate of betel-quid use was classified into none, low (3.5 times/d), and high (>3.5 times/d) categories. Moreover, among the risk factors and components of the metabolic syndrome, significant sex-by-tertile of betel-quid use interactions for body mass index, alcohol drinking, SBP, DBP, high BP, and dietary intakes of carbohydrates and vegetables were observed. Thus, demographic and laboratory characteristics of the participants were reported separately for the men and women.
Demographic and laboratory characteristics of NAHSIT participants by categories of betel use
The findings for features of the metabolic syndrome and its risk factors are shown in Table 1 by categories of betel-quid use. Note that there was a linear trend with increasing smoking, alcohol drinking, and triacylglycerol and with decreasing age and fruit intake across increasing betel-quid use categories. In contrast, there was a linear trend with increasing SBP, DBP, and body mass index and with decreasing carbohydrate intake across increasing betel-quid use categories only in the women.
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TABLE 1. Demographic and laboratory characteristics of the Nutrition and Health Survey in Taiwan participants by different betel-quid use categories1
Note that the apparent number of women chewers was only 25 (1066 x 2.3%). However, the prevalence of betel-quid chewing for the women (2.3%) was a weighted estimate. Thus, the actual number of women chewers was 82 (n = 32 in the low group and 50 in the high group), and the crude prevalence of betel-quid chewing for the women was 7.7% (n = 82 of 1066).
Sex-specific demographic characteristics in the participants with or without the metabolic syndrome
The overall prevalence of the metabolic syndrome was 9.9% (10.1% for the men compared with 9.7% for the women, P = 0.86). Moreover, a logistic regression analysis showed that the prevalence of the metabolic syndrome increased with age in both sexes [odds ratio (OR) associated with 10-y increase in age: 1.008; 95% CI: 1.005, 1.01; P < 0.001). Note that the women with the metabolic syndrome ate less fruit and were less likely to drink or exercise than women without the metabolic syndrome (data not shown). These relations were not observed in the men. In contrast, no significant differences for any other dietary factors were observed in both sexes (data not shown).
Prevalence of risk factors and the 5 components of the metabolic syndrome in NAHSIT participants
The sex-specific prevalence of the risk factors and the 5 components used to define the metabolic syndrome in the present study are shown in Table 2. The prevalence of smoking, alcohol drinking, and high BP was higher in the men than in the women. Conversely, the prevalence of abdominal obesity, low HDL-cholesterol, and hyperglycemia was higher in the women than in the men, whereas physical activity and the prevalence of hypertriacylglycerolemia were not significantly different between the men and women.
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TABLE 2. Sex-specific prevalence of the 5 components of the metabolic syndrome and characteristics of the risk factors in the Nutrition and Health Survey in Taiwan participants1
Betel-quid use category as a risk factor for each of the 5 components used to define the metabolic syndrome
In the above univariate analyses, the association between betel-quid use and the metabolic syndrome was confounded by the imbalances of many risk factors between betel-quid users and nonusers. Thus, multivariate analyses were adjusted for other metabolic syndrome risk factors to ascertain the role of betel-quid use in the development of the metabolic syndrome. The results for the NAHSIT participants in whom the 5 components of metabolic syndrome were analyzed as continuous variables are shown in Table 3. A linear trend with increasing serum triacylglycerol was observed across increasing betel-quid use categories. In contrast, a linear trend with increasing waist circumference, SBP, and DBP across increasing betel-quid use categories was observed only in the women.
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TABLE 3. Multiple linear regression analyses of betel-quid use categories as a risk factor for each of the 5 components of the metabolic syndrome1
The results for the NAHSIT participants in whom the 5 components of the metabolic syndrome were analyzed as categorical variables are shown in Table 4. A linear trend with increasing prevalence of high BP across increasing betel-quid use categories was observed only in the women.
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TABLE 4. Multiple logistic regression analyses of betel-quid use categories as a risk factor for the metabolic syndrome and its 5 components1
Note that no significant interaction between age and betel-quid use categories was observed (Table 3 and Table 4). Namely, the relation between betel-quid use categories and each of the 5 components of the metabolic syndrome did not differ significantly with age.
Daily rate of betel-quid use as a risk factor for each of the 5 components used to define the metabolic syndrome
The results for the NAHSIT participants in whom the daily rate of betel-quid use was analyzed as a continuous variable are shown in Table 5. The daily rate of betel-quid use was independently and positively associated with waist circumference, serum triacylglycerol, and SBP. Betel-quid use was also independently and positively associated with abdominal obesity, hypertriacylglycerolemia, and high BP, but not with low HDL cholesterol or hyperglycemia. Note that the size of the coefficient or OR of a continuous variable is dependent on the unit (29), which, in this case, was 10 times/d (the third quartile of betel-quid use).
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TABLE 5. Linear regression and logistic regression analyses of the daily rate of betel-quid use as a risk factor for each of the 5 components of the metabolic syndrome1
No significant interaction between age and the daily rate of betel-quid use was observed. Namely, the relation between the daily rate of betel-quid use and each of the 5 components of the metabolic syndrome did not differ significantly with age.
Betel-quid use category as a risk factor for the metabolic syndrome
When betel-quid use was analyzed as a categorical variable, neither low nor high use categories were significantly associated with the metabolic syndrome for either sex. Additionally, there was no linear trend with increasing prevalence of metabolic syndrome across increasing betel-quid use categories (Table 1). Moreover, there was no significant interaction between age and betel-quid use categories. Namely, the relation between betel-quid use category and metabolic syndrome did not differ significantly with age.
Daily rate of betel-quid use as a risk factor for the metabolic syndrome
When betel-quid use was analyzed as a continuous variable, the daily rate of betel-quid use was associated with the metabolic syndrome (OR associated with a rate of betel-quid consumption of 10 times/d: 1.31; 95% CI: 1.12, 1.55; P = 0.003) in both the men and women. However, there was no significant interaction between age and the daily rate of betel-quid use. Namely, the relation between the daily rate of betel-quid use and the metabolic syndrome did not differ significantly with age.
DISCUSSION
The present study appears to be the first to show that, other than hyperglycemia and central obesity, the daily rate of betel-quid use is an independent risk factor for features of the metabolic syndrome. In view of the enormous world population (10%) that uses betel quid (2, 8) and the effect of the metabolic syndrome on global health (4), our finding has important epidemiologic implications.
The results were different when we analyzed betel-quid use as either a categorical or a continuous variable. The results of continuous variables are more reliable because the categorization of continuous variables leads to a loss of information (30). Thus, we found that the daily rate of betel-quid use was associated with 3 of the 5 components of the metabolic syndrome by multiple logistic regression: abdominal obesity, hypertriacylglycerolemia, and high BP (categorical variables). Similarly, it was associated with 3 of the 5 components of metabolic syndrome by multiple linear regression: waist circumference, serum triacylglycerol, and SBP (continuous variables).
Note that the effect of betel-quid use was independent of the other risk factors, which were examined by using multiple logistic regression analysis. However, due to the complex nature of independent risk factor research in epidemiology, we cannot dismiss the possibility of residual confounding by other as yet unknown factors (31) that may emerge in future studies.
The mechanism of betel-induced abdominal obesity and hypertriacylglycerolemia is not known. However, a study conducted in India found that arecoline suppressed appetite while increasing postprandial carbohydrate use in 15 men (32). Thus, betel-induced abdominal obesity is likely to depend on factors other than arecoline. On the other hand, betel-quid use may increase serum triacylglycerol secondary to the induction of central obesity.
The mechanism via which betel induces high BP is also not known. However, some studies found that betel-quid use acutely increased BP, probably by activating sympathetic nerves (3), which is a feature of essential hypertension (33). Interestingly, betel quid-induced sympathetic activation is also mediated by factors other than arecoline, a parasympathomimetic agent (3).
Our finding that betel-quid use was not significantly associated with hyperglycemia contrasts those of 3 previous studies (8, 9, 34). The first study, which was conducted in New Guinea (n = 769), showed that betel-quid use was associated with DM (9). However, that study defined DM as fasting capillary blood glucose 7 mmol/L, which is different from the World Health Organization definition of DM (fasting venous or capillary whole blood glucose 6.1 mmol/L) (25). Moreover, the dose-dependent effects of betel-quid use were not studied, in contrast to the present study. The second study, which was conducted in Taiwan (n = 14 816), showed that betel-quid use was associated with hyperglycemia and DM in men (34). However, the 2 studies did not exclude specimens with hemolysis, and hemolysis affects the testing of blood glucose concentrations (35). Moreover, the researchers did not exclude persons who fasted <8 h, but the definition of hyperglycemia depends on an adequate fasting time. In fact, we found that betel-quid use was independently and positively associated with DM (OR: 2.4; 95% CI: 1.5, 4.0; P = 0.002) if we increased the sample size to 2215 by including persons who fasted <8 h and blood specimens with hemolysis (n = 250). Thus, the reduction of sample size would itself tend to reduce the chance of detecting a significant relation between betel-quid use and hyperglycemia. A third study conducted in Bangladeshis (n = 993) showed that betel-quid use was associated with hyperglycemia only in women (8). The first and third studies had a smaller sample size, whereas the second study had a bigger sample size, than did our study. However, in contrast with our population-based study, the other 3 studies were community-based studies, which thereby lack generalizability to the population.
Interestingly, one study conducted in Taiwan showed that the prevalence of betel-quid use in patients with DM was 13.2% (36). In contrast, the prevalence of betel-quid use in patients with and without DM in our study was 14% and 16.2% (P = 0.56), respectively.
One confounding factor is that the fasting glucose concentration alone is not sensitive enough for the detection of either impaired glucose tolerance or DM. For example, studies conducted in Canada and Taiwan showed that fasting glucose concentrations missed 16.6–23% of persons with impaired glucose tolerance or DM (37, 38). Additionally, betel quid (which contains arecoline) is often chewed with Piper betle leaves, which contain short-lived hypoglycemic agents (39) and hydroxychavicol (40). Note that both arecoline and hydroxychavicol have short-term hypoglycemic activities (40, 41).
We speculate that betel quid induces the metabolic syndrome, insulin resistance, or both by the several mechanisms. First, betel quid induces sympathetic activation (3), which is present in insulin resistance and the metabolic syndrome (33). Second, betel quid is associated with central obesity, itself a major risk factor for insulin resistance and the metabolic syndrome (42). Third, arecal alkaloids lead to -aminobutyric acid receptor blockade (43), and defective -aminobutyric acid neuromodulation was suggested to be a mechanism that induces insulin resistance (44). Fourth, betel quid induces oxidative stress (45) and inflammation (46), 2 conditions causally linked to insulin resistance (5, 47). Finally, specific arecal nitrosamines may be diabetogenic, as are various structurally similar nitroso compounds such as Streptozotocin, the structure of which leads to the targeting of islet ß cell glucose receptors (8). However, betel quid-induced hyperglycemia may be masked by the effects of Piper betle leaves.
In conclusion, the daily rate of betel-quid use was independently and positively associated with the metabolic syndrome and 3 of its components (abdominal obesity, hypertriacylglycerolemia, and high BP) in a dose-dependent manner. Moreover, we found that, although men were more likely to be betel users than women and the prevalence of 4 of the 5 components of the metabolic syndrome were different between the sexes, the prevalence of the metabolic syndrome was not significantly different between the men and women.
ACKNOWLEDGMENTS
We thank Academia Sinica for data distribution and for their assistance.
J-YG was involved in the study design and analysis. L-YC was involved in the data collection and statistical analysis. H-CC was involved in the fund raising, study design, and collaborative analysis. None of the authors had any conflicts of interest.
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