Background: Maté tea is a nonalcoholic infusion widely consumed in southern South America, and may increase risk of esophageal squamous cell carcinoma (ESCC) and other cancers due to polycyclic aromatic hydrocarbons (PAH) and/or thermal injury.

Methods: We pooled two case–control studies: a 1988 to 2005 Uruguay study and a 1986 to 1992 multinational study in Argentina, Brazil, Paraguay, and Uruguay, including 1,400 cases and 3,229 controls. We computed ORs and fitted a linear excess OR (EOR) model for cumulative maté consumption in liters/day–year (LPDY).

Results: The adjusted OR for ESCC with 95% confidence interval (CI) by ever compared with never use of maté was 1.60 (1.2–2.2). ORs increased linearly with LPDY (test of nonlinearity; P = 0.69). The estimate of slope (EOR/LPDY) was 0.009 (0.005–0.014) and did not vary with daily intake, indicating maté intensity did not influence the strength of association. EOR/LPDY estimates for consumption at warm, hot, and very hot beverage temperatures were 0.004 (−0.002–0.013), 0.007 (0.003–0.013), and 0.016 (0.009–0.027), respectively, and differed significantly (P < 0.01). EOR/LPDY estimates were increased in younger (<65) individuals and never alcohol drinkers, but these evaluations were post hoc, and were homogeneous by sex.

Conclusions: ORs for ESCC increased linearly with cumulative maté consumption and were unrelated to intensity, so greater daily consumption for shorter duration or lesser daily consumption for longer duration resulted in comparable ORs. The strength of association increased with higher maté temperatures.

Impact: Increased understanding of cancer risks with maté consumption enhances the understanding of the public health consequences given its purported health benefits. Cancer Epidemiol Biomarkers Prev; 23(1); 107–16. ©2013 AACR.

Maté tea is an infusion made from leaves of the tree Ilex paraguariensis, a member of the Aquifoliaceae (holly) family (1, 2). It is a nonalcoholic beverage consumed throughout southern South America, and is gaining broader acceptance in other areas of the world as a tea and dietary supplement based on purported health benefits, such as lowered cholesterol levels, improved cardiovascular health, and obesity management (2, 3). However, studies have linked maté consumption with esophageal squamous cell carcinoma (ESCC), as well as cancers of the oral cavity, pharynx, larynx, lung, kidney, and bladder (4–13). The International Agency for Research on Cancer (IARC) designated hot maté drinking a probable human carcinogen (group IIA; 1). Proposed carcinogenic mechanisms include thermal injury from repeated high temperature exposure and exposure to polycyclic aromatic hydrocarbons (PAH), a production-related contaminant (1, 14–17).

Although studies have associated maté consumption with ESCC, there has been no quantitative evaluation of the relationship between ESCC and total exposure, as measured by liters/day–year (LPDY), the product of lifetime mean liters/day (LPD) and years of consumption. In addition, evaluations of potential effect modifiers, such as age, sex, cigarette smoking, and alcohol consumption, have been limited.

We pooled data from two large case–control studies of ESCC, one an aggregation of five component studies. Our goals were to evaluate (i) the quantitative relationship between ESCC and LPDY of maté consumption, (ii) the impact of LPD on the strength of association, and (iii) potential effect modifiers, including maté temperature, sex, age, cigarette smoking, and alcohol consumption.

Study data

Uruguay case–control study.

Cases included patients who were incident between 1990 and 2004, ages 35 to 85 years in medical records of the Oncology Institute Cancer Registry with histopathologically confirmed ESCC. Patients had to be mentally competent for interview, diagnosed within the previous 4 months and resident in Uruguay for ≥10 years (5).

Controls included patients admitted to the same institution during the same period with conditions unrelated to tobacco smoking and alcohol consumption and with comparable residency, and were frequency matched to cases by age and sex. Within the frequency matched groups, investigators enrolled greater numbers of female controls.

Interviews occurred shortly after hospital admittance. Questionnaires collected information on demographic and socioeconomic characteristics, personal and family history, maté drinking, alcohol consumption, and tobacco smoking. For alcohol intake, we calculated mL of ethanol per day by summing ethanol per day for a standard serving of each beverage type.

IARC multinational case–control study.

Between 1986 and 1992, investigators conducted four hospital-based case–control studies of ESCC in Argentina, Brazil, Paraguay, and Uruguay, the latter independent of the Uruguay study described above. Investigators further extended this Uruguay component, which represented a fifth study. IARC coordinated the studies, which we have collectively denoted as the IARC multinational study. Results have been published previously (4, 18–22). The components used similar protocols and questionnaires, allowing for local adaptations.

Cases included histologically confirmed patients with ESCC (the Paraguay component also accepted cytologic or radiologic diagnoses), diagnosed within the previous 3 to 6 months, resident in the area for ≥5 years and competent for interview. In Argentina, cases were ascertained from the 10 main hospitals of greater La Plata (19). In Brazil, cases were ascertained from the 8 main hospitals and 3 radiotherapy units of Port Alegre and Pelotas, at the time the 2 largest cities in the state of Rio Grande do Sul (21). In Uruguay, cases came from the 4 main hospitals in Montevideo, which covered about 45% of the population of the city and about 55% of the population of the rest of the country (4, 22). Investigators checked identification numbers and names to ensure there was no duplication or overlap of cases among the various Uruguay component studies. In Paraguay, subjects were ascertained from the 4 hospitals, private clinics, pathology laboratories, and radiology clinics in Asuncion (20). The case participation rate in all studies was high (90.0%–99.2%).

Controls who were admitted during the same period were frequency matched to cases on hospital, gender, age, and residence period, and included patients with diseases unrelated to alcohol or tobacco. Diagnostic categories were given previously (13, 19–22). Investigators replaced controls that refused to participate, except in Paraguay, although control participation rate was high (97.0%).

Questionnaires ascertained information on demographic and socioeconomic characteristics, tobacco smoking, alcohol drinking, and consumption of hot beverages, including maté, tea, and coffee. Beverage temperatures were self-assessed. Proxy interviews were not accepted.

The Institutional Review Board or Research Ethics Committee for each study approved data collection and, if required, participation in the pooling.

Statistical analysis

For categorical variables, we computed ORs using standard logistic regression (23). For continuous LPDY, d, ORs were not log-linear. We thus fitted the model |${\rm OR}(d, z)\, = \,\exp (\alpha z) \times {\rm OR}(d)$|⁠, where

z was a vector of adjustment variables with parameters α, whereas β was the excess OR per LPDY (EOR/LPDY), a measure of strength of association. We replaced d with |$d \times \exp \{\theta {\rm ln}(d)\} \, = \,d^{1 + \theta}$| and used the likelihood ratio to test no departure from linearity |${\rm (}\theta \,{\rm =}\,{\rm 0)}$|⁠.

We evaluated effect modification by examining variations in the trend of ORs by LPDY across a categorical factor (f). For factor f with S categories, s = 1,…,S, we fitted

where βs parameters replaced β and ds equaled d within category s and zero otherwise. If f was unrelated to maté consumption, for example, sex, then z included f as an adjustment variable. If f was related to maté consumption, for example, LPD or beverage temperature, then z did not include f because no adjustment in never-drinkers was required. We compared deviances for model (1) and model (2) to test homogeneity of slopes, |$\beta _1 \, = \, \ldots \, = \,\beta _s \, = \,\beta$|⁠, i.e., no effect modification. We replaced ds with |$d_s \times \exp \{\theta _s {\rm ln}(d_s)\}$| to test no departure from linearity within category |$(\theta _s \, = \,0)$|⁠.

We used the Epicure program to estimate ORs and 95% confidence intervals (CI), fit models, and derive likelihood-based CIs for β estimates (24).

Model adjustment factors

Analyses adjusted for joint categories of study/component (6 levels), cigarette smoking in pack-years (0, <30, 30–39, 40–59, 60–79, and ≥80) and alcohol consumption in mL ethanol/d–y (0, <1,170, 1,170–2,439, 2,440–4,679, 4,680–9,359, and ≥9,360), and for age (<55, 55–64, 65–74, and ≥75 years), sex, cigarettes/d (<10, 10–19, 20–29, and ≥30), mL ethanol per day (<32, 33–77, 78–155, and ≥156), years of education (<3, 3–5, and ≥6 for the Uruguay study and <4, 4–6, and ≥7 for the IARC study), and for the Uruguay study income (<US$120, ≥US$120, missing) and residency (urban, rural).

ORs by LPDY increased linearly in the IARC data and in the Uruguay data, but only among maté drinkers in the latter. For Uruguay data, we defined a fixed offset to adjust for ever and never maté drinkers using the model |${\rm OR}(d)\, = \,\exp \{\alpha {\rm I}(d)\} \times \{1 + \beta d\}$|⁠, where I(d) equaled one for d > 0 and zero otherwise. The estimate, |$\exp \{\alpha \}$|⁠, was 2.42 (95% CI, 1.5–2.9), and represented the LPDY-adjusted OR of ever relative to never-consumed maté. A detailed examination identified a small subgroup responsible for the excess. The subgroup included male (3 cases and 53 controls) and female (1 case and 61 controls) urban residents who abstained from alcohol, with ORs for ever-consumed maté of 4.24 (95% CI, 1.1–16.7) and 13.8 (95% CI, 1.8–105.8), respectively. We fixed the offset to −ln(4.24) and −ln(13.8) for Uruguay male and female urban residents who never consumed alcohol or maté and zero otherwise. The offset essentially served to replace the observed case to control odds with the expected odds, eliminating the nonlinearity. See details in Supplementary Materials and comments in the Discussion. The use of a fixed offset was an a priori decision, due to a concern about the possibility of broad impact on ORs from this small, highly influential subgroup. Alternatively, we could have introduced an indicator variable for this subgroup and estimated its effect, or have omitted these subjects. Regardless of approach, inference was unaffected.

ORs for adjustment and other factors

There were 1,400 cases (1,085 males and 315 females) and 3,229 controls (2,279 males and 950 females; Table 1). ORs increased with pack-years of smoking, cigarettes/d, cumulative alcohol consumption, and alcohol intensity in both studies (P < 0.01). ORs increased with use of mixed/black-only tobacco cigarettes compared with blond-only tobacco cigarettes, achieving statistical significance in the IARC study and the pooled data.

Table 1.

ORs by characteristics of data from the Uruguay and IARC multinational case–control studies

Uruguay studyIARC study
CasesControlsORa (95% CI)CasesControlsORa (95% CI)
Subjects 612 1,518  788 1,711  
Study componentb 
 Argentina    125 254  
 Brazil    159 323  
 Paraguay    122 368  
 Uruguay I    247 497  
 Uruguay II    135 269  
Ageb 
 <55 89 227  145 334  
 55–64 151 342  261 550  
 65–74 218 563  250 581  
 ≥75 154 386  132 246  
Sexb 
 Males 465 930  620 1,349  
 Female 147 588  168 362  
Education 
 Ic 168 425 1.00 423 755 1.00 
 II 225 571 1.21 (0.9–1.6) 320 803 0.75 (0.6–0.9) 
 III 219 522 1.55 (1.2–2.1) 45 153 0.54 (0.4–0.8) 
Pd   0.01   <0.01 
Income/monthe 
 <$US120 288 673 1.00    
 ≥$US120 258 665 0.94 (0.7–1.2)    
 Missing 66 180 0.72 (0.5–1.0)    
P   0.57    
Residencee 
 Urban 433 1,168 1.00    
 Rural 179 350 1.38 (1.1–1.8)    
P   0.01    
Pack-years 
 0 133 743 1.00 138 611 1.00 
 <30 113 363 1.81 (1.3–2.6) 250 598 2.07 (1.5–2.8) 
 30–39 51 107 2.80 (1.8–4.4) 78 119 3.31 (2.2–5.0) 
 40–59 141 181 4.00 (2.7–5.8) 159 187 3.93 (2.7–5.6) 
 60–79 74 60 5.91 (3.7–9.5) 62 79 3.06 (1.9–4.9) 
 ≥80 100 64 8.09 (5.2–12.6) 101 117 3.05 (2.0–4.6) 
P   <0.01   <0.01 
Cigarettes/d 
 0 133 743 1.00 138 611 1.00 
 1–10 51 186 1.64 (1.1–2.5) 135 336 1.95 (1.4–2.7) 
 10–19 88 263 1.82 (1.2–2.7) 144 257 2.86 (2.0–4.1) 
 20–29 160 214 3.88 (2.7–5.6) 201 279 3.35 (2.4–4.7) 
 ≥30 180 112 8.30 (5.6–12.2) 170 228 2.89 (2.0–4.1) 
P   <0.01   <0.01 
Type of tobaccof 
 Blond-only 164 316 1.00 230 509 1.00 
 Mixed/black-only 273 373 1.19 (0.9–1.6) 356 508 1.62 (1.2–2.1) 
P   0.24   <0.01 
Ethanol mL/d–y 
 0 210 842 1.00 172 761 1.00 
 1–1,169 41 142 0.94 (0.6–1.4) 143 374 2.01 (1.5–2.7) 
 1,170–2,339 52 147 1.03 (0.7–1.5) 110 192 3.05 (2.2–4.3) 
 2,340–4,679 78 161 1.26 (0.9–1.8) 133 191 3.99 (2.8–5.6) 
 4,680–9,359 121 160 2.00 (1.4–2.8) 113 124 5.46 (3.8–7.9) 
 ≥9,360 110 66 3.73 (2.5–5.6) 117 69 10.0 (6.7–15.1) 
P   <0.01   <0.01 
Ethanol mL/d 
 0 210 842 1.00 172 761 1.00 
 1–32 50 161 1.03 (0.7–1.5) 146 368 2.10 (1.6–2.8) 
 32–77 77 221 0.92 (0.6–1.3) 136 267 2.73 (2.0–3.7) 
 78–155 110 169 1.72 (1.2–2.4) 171 201 5.21 (3.7–7.2) 
 ≥156 165 125 3.10 (2.2–4.4) 163 114 8.20 (5.7–11.7) 
P   <0.01   <0.01 
Uruguay studyIARC study
CasesControlsORa (95% CI)CasesControlsORa (95% CI)
Subjects 612 1,518  788 1,711  
Study componentb 
 Argentina    125 254  
 Brazil    159 323  
 Paraguay    122 368  
 Uruguay I    247 497  
 Uruguay II    135 269  
Ageb 
 <55 89 227  145 334  
 55–64 151 342  261 550  
 65–74 218 563  250 581  
 ≥75 154 386  132 246  
Sexb 
 Males 465 930  620 1,349  
 Female 147 588  168 362  
Education 
 Ic 168 425 1.00 423 755 1.00 
 II 225 571 1.21 (0.9–1.6) 320 803 0.75 (0.6–0.9) 
 III 219 522 1.55 (1.2–2.1) 45 153 0.54 (0.4–0.8) 
Pd   0.01   <0.01 
Income/monthe 
 <$US120 288 673 1.00    
 ≥$US120 258 665 0.94 (0.7–1.2)    
 Missing 66 180 0.72 (0.5–1.0)    
P   0.57    
Residencee 
 Urban 433 1,168 1.00    
 Rural 179 350 1.38 (1.1–1.8)    
P   0.01    
Pack-years 
 0 133 743 1.00 138 611 1.00 
 <30 113 363 1.81 (1.3–2.6) 250 598 2.07 (1.5–2.8) 
 30–39 51 107 2.80 (1.8–4.4) 78 119 3.31 (2.2–5.0) 
 40–59 141 181 4.00 (2.7–5.8) 159 187 3.93 (2.7–5.6) 
 60–79 74 60 5.91 (3.7–9.5) 62 79 3.06 (1.9–4.9) 
 ≥80 100 64 8.09 (5.2–12.6) 101 117 3.05 (2.0–4.6) 
P   <0.01   <0.01 
Cigarettes/d 
 0 133 743 1.00 138 611 1.00 
 1–10 51 186 1.64 (1.1–2.5) 135 336 1.95 (1.4–2.7) 
 10–19 88 263 1.82 (1.2–2.7) 144 257 2.86 (2.0–4.1) 
 20–29 160 214 3.88 (2.7–5.6) 201 279 3.35 (2.4–4.7) 
 ≥30 180 112 8.30 (5.6–12.2) 170 228 2.89 (2.0–4.1) 
P   <0.01   <0.01 
Type of tobaccof 
 Blond-only 164 316 1.00 230 509 1.00 
 Mixed/black-only 273 373 1.19 (0.9–1.6) 356 508 1.62 (1.2–2.1) 
P   0.24   <0.01 
Ethanol mL/d–y 
 0 210 842 1.00 172 761 1.00 
 1–1,169 41 142 0.94 (0.6–1.4) 143 374 2.01 (1.5–2.7) 
 1,170–2,339 52 147 1.03 (0.7–1.5) 110 192 3.05 (2.2–4.3) 
 2,340–4,679 78 161 1.26 (0.9–1.8) 133 191 3.99 (2.8–5.6) 
 4,680–9,359 121 160 2.00 (1.4–2.8) 113 124 5.46 (3.8–7.9) 
 ≥9,360 110 66 3.73 (2.5–5.6) 117 69 10.0 (6.7–15.1) 
P   <0.01   <0.01 
Ethanol mL/d 
 0 210 842 1.00 172 761 1.00 
 1–32 50 161 1.03 (0.7–1.5) 146 368 2.10 (1.6–2.8) 
 32–77 77 221 0.92 (0.6–1.3) 136 267 2.73 (2.0–3.7) 
 78–155 110 169 1.72 (1.2–2.4) 171 201 5.21 (3.7–7.2) 
 ≥156 165 125 3.10 (2.2–4.4) 163 114 8.20 (5.7–11.7) 
P   <0.01   <0.01 

aORs and 95% CIs from logistic regression that included all variables in the table as well as cumulative and LPD of maté consumption. Models included a sex-specific fixed offset variable for the Uruguay data to account for differential effects of maté consumption in urban, never alcohol consumers. Adjustment variables for ORs by pack-years (cigarettes/d) omit cigarettes/d (pack-years). Adjustment variables for ORs by ethanol/d–y (ethanol/d) omit ethanol/d (ethanol/d–y).

bStudy, age, and sex were design variables and OR were omitted.

cFor Uruguay: levels represent 0–2, 3–5, and 6+ years; and for IARC, levels represent 0–3, 4–6, and 7+ years.

dP value for one degree of freedom score test of trend.

eInformation collected only for the Uruguay study.

fMales only. ORs relative to blond tobacco only smokers and adjusted for variables in the table.

Marginal ORs for maté consumption

In the Uruguay study, 95.6% of cases and 87.5% of controls and in the IARC study 92.9% of cases and 87.0% of controls ever drank maté. Among drinkers, Uruguay cases had greater mean intensity, duration, and total intake (1.2 LPD, 52.3 years, and 64.8 LPDY, respectively) compared with IARC cases (1.1 LPD, 47.0 years, and 54.3 LPDY). For controls, these maté-related metrics were also greater in the Uruguay study (1.1, 50.8, and 55.3) than in the IARC study (0.9, 44.9, and 40.8). Intake for the two Uruguay components of the IARC study was comparable with intake for the Uruguay study, and generally exceeded intake for the Argentina, Brazil, and Paraguay components of the IARC study (see Supplementary Table SB1).

The overall adjusted OR for ESCC by ever compared with never use of maté was 1.60 (95% CI, 1.2–2.2; Table 2), ORs by cumulative maté consumption and maté intensity increased in each study and the pooled data, with stronger associations in the IARC data. The offset modification greatly influenced the Uruguay results, as without the offset ORs were 1.0, 2.3, 2.8, 3.5, 2.0, and 3.3 for LPDY (P < 0.01) and 1.0, 2.5 2.8, 3.2, and 2.6 for LPD (P = 0.04) for their respective categories.

Table 2.

Data from the Uruguay and IARC multinational case–control studies

Uruguay studyIARC studyPooled data
CasesControlsORa (95% CI)CasesControlsORa (95% CI)OR (95% CI)
Never-drinkerb 27 190 1.00 56 223 1.00 1.00 
Ever-drinker 583 1,311 1.56 (0.9–2.6) 725 1,480 1.61 (1.1–2.3) 1.60 (1.2–2.2) 
Cumulative maté consumption (LPDY) 
 1–29 101 340 1.29 (0.8–2.2) 248 675 1.38 (0.9–2.1) 1.34 (1.0–1.8) 
 30–49 133 319 1.58 (0.9–2.7) 167 389 1.37 (0.9–2.1) 1.45 (1.0–2.0) 
 50–69 178 334 1.95 (1.1–3.3) 134 223 2.01 (1.3–3.1) 1.99 (1.4–2.8) 
 70–99 67 178 1.12 (0.6–2.0) 82 109 2.54 (1.5–4.2) 1.64 (1.1–2.4) 
 ≥100 106 157 1.89 (1.1–3.3) 101 92 3.60 (2.2–6.0) 2.53 (1.8–3.6) 
Pc   0.08   <0.01 <0.01 
Mate intake (LPD) 
 0.1–1.0 149 455 1.41 (0.8–2.4) 318 861 1.28 (0.9–1.9) 1.33 (1.0–1.8) 
 1.0–1.9 299 661 1.58 (1.0–2.6) 264 481 1.85 (1.2–2.8) 1.71 (1.3–2.3) 
 2.0–2.9 104 169 1.82 (1.0–3.2) 103 108 3.14 (1.9–5.4) 2.38 (1.7–3.4) 
 ≥3.0 33 43 1.46 (0.7–3.0) 47 38 4.69 (2.5–8.8) 2.77 (1.7–4.4) 
P   0.37   <0.01 <0.01 
Temperature 
 Warm 48 212 0.93 (0.5–1.7) 120 285 1.38 (0.9–2.2) 1.20 (0.8–1.7) 
 Hot 417 914 1.64 (1.0–2.7) 512 1,085 1.53 (1.0–2.2) 1.61 (1.2–2.2) 
 Very hot 120 202 1.79 (1.0–3.1) 93 110 2.61 (1.6–4.2) 2.15 (1.5–3.1) 
P   <0.01   <0.01 <0.01 
Years since last matéd 
 0 523 1,201 1.00 630 1303 1.00 1.00 
 1–4 37 50 1.50 (0.9–2.5) 44 70 1.41 (0.9–2.2) 1.45 (1.0–2.0) 
 5+ 23 60 0.87 (0.5–1.5) 51 107 1.04 (0.7–1.6) 0.96 (0.7–1.3) 
Pd   0.47   0.38 0.22 
Age, first matéd 
 <12 239 362 1.00 238 438 1.00 1.00 
 12–16 217 623 0.44 (0.3–0.6) 234 380 1.31 (1.0–1.8) 0.74 (0.6–0.9) 
 ≥17 127 326 0.58 (0.4–0.8) 253 662 0.93 (0.7–1.3) 0.71 (0.6–0.9) 
P   <0.01   0.55 <0.01 
Uruguay studyIARC studyPooled data
CasesControlsORa (95% CI)CasesControlsORa (95% CI)OR (95% CI)
Never-drinkerb 27 190 1.00 56 223 1.00 1.00 
Ever-drinker 583 1,311 1.56 (0.9–2.6) 725 1,480 1.61 (1.1–2.3) 1.60 (1.2–2.2) 
Cumulative maté consumption (LPDY) 
 1–29 101 340 1.29 (0.8–2.2) 248 675 1.38 (0.9–2.1) 1.34 (1.0–1.8) 
 30–49 133 319 1.58 (0.9–2.7) 167 389 1.37 (0.9–2.1) 1.45 (1.0–2.0) 
 50–69 178 334 1.95 (1.1–3.3) 134 223 2.01 (1.3–3.1) 1.99 (1.4–2.8) 
 70–99 67 178 1.12 (0.6–2.0) 82 109 2.54 (1.5–4.2) 1.64 (1.1–2.4) 
 ≥100 106 157 1.89 (1.1–3.3) 101 92 3.60 (2.2–6.0) 2.53 (1.8–3.6) 
Pc   0.08   <0.01 <0.01 
Mate intake (LPD) 
 0.1–1.0 149 455 1.41 (0.8–2.4) 318 861 1.28 (0.9–1.9) 1.33 (1.0–1.8) 
 1.0–1.9 299 661 1.58 (1.0–2.6) 264 481 1.85 (1.2–2.8) 1.71 (1.3–2.3) 
 2.0–2.9 104 169 1.82 (1.0–3.2) 103 108 3.14 (1.9–5.4) 2.38 (1.7–3.4) 
 ≥3.0 33 43 1.46 (0.7–3.0) 47 38 4.69 (2.5–8.8) 2.77 (1.7–4.4) 
P   0.37   <0.01 <0.01 
Temperature 
 Warm 48 212 0.93 (0.5–1.7) 120 285 1.38 (0.9–2.2) 1.20 (0.8–1.7) 
 Hot 417 914 1.64 (1.0–2.7) 512 1,085 1.53 (1.0–2.2) 1.61 (1.2–2.2) 
 Very hot 120 202 1.79 (1.0–3.1) 93 110 2.61 (1.6–4.2) 2.15 (1.5–3.1) 
P   <0.01   <0.01 <0.01 
Years since last matéd 
 0 523 1,201 1.00 630 1303 1.00 1.00 
 1–4 37 50 1.50 (0.9–2.5) 44 70 1.41 (0.9–2.2) 1.45 (1.0–2.0) 
 5+ 23 60 0.87 (0.5–1.5) 51 107 1.04 (0.7–1.6) 0.96 (0.7–1.3) 
Pd   0.47   0.38 0.22 
Age, first matéd 
 <12 239 362 1.00 238 438 1.00 1.00 
 12–16 217 623 0.44 (0.3–0.6) 234 380 1.31 (1.0–1.8) 0.74 (0.6–0.9) 
 ≥17 127 326 0.58 (0.4–0.8) 253 662 0.93 (0.7–1.3) 0.71 (0.6–0.9) 
P   <0.01   0.55 <0.01 

aORs from logistic regression for the maté consumption variable, adjusted by smoking (pack-years, cigarettes/d), alcohol consumption (drink-years, drinks/d), age, sex, sex by education, and for Uruguay income and urban/rural residence. Pooled ORs further adjusted for study. Models included a sex-specific fixed offset variable for the Uruguay data to account for differential effects of maté consumption in urban, never alcohol consumers. Number of cases and controls differ slightly from Table 1 due to missing data.

bReferent category, except where noted. Number of cases and controls vary due to missing data.

cP value for the score test of no trend.

dORs and P values computed among maté drinkers only relative to the lowest category.

We evaluated ORs by self-reported maté temperature, warm, hot, or very hot, and found that ORs increased significantly with temperature, although the OR for warm maté consumption was not statistically significant. Few users ceased consumption (8.4% and 12.0% in Uruguay and IARC controls, respectively) and ORs varied inconsistently with years since cessation. Among drinkers, ORs were increased at younger age at first use in the Uruguay data and unrelated in the IARC data.

OR trends were homogeneous across studies for maté temperature (P = 0.85) and cessation (P = 0.84), but differed for cumulative intake, intensity and age at first use (P < 0.01; not shown).

Joint ORs for cumulative LPDY and LPD of maté consumption

We first examined LPD as a modifier of the LPDY association that is whether the strength of association varied by intensity or alternatively whether for a fixed total LPDY low intensity for long duration resulted in greater, equal, or lesser risk compared with high intensity for short duration. For joint categories of LPDY and LPD, ORs relative to never-drinkers increased with LPDY within each LPD category (Fig. 1A–D, solid symbol), with trends consistent with linearity, except for 1.0–1.9 LPD (P = 0.03). EOR/LPDY estimates for the 4 LPD categories were 0.001, 0.006, 0.008, and 0.007, respectively, revealing minimal variation in strength of association (test of homogeneity; P = 0.35). Across the full range of continuous LPDY, a linear relationship described maté-related ORs (Fig. 1E; P = 0.76 for the test of no departure from linearity). The EOR/LPDY estimate with 95% CI was 0.009 (0.005–0.014). After omitting low-intensity drinkers (LPD < 0.5), model fit improved slightly (dash line), and the EOR/LPDY estimate was 0.012 (95% CI, 0.007–0.020).

Figure 1.

ORs for cumulative maté consumption in LPDY within categories of mean daily intake in LPD (A < 1.0; B 1.0–1.9; C 2.0–2.9; D ≥ 3.0) and overall (E), and fitted linear models for the EOR using all data (solid line) or restricted data (never and ≥0.5 LPD maté drinkers). Pooled data from the Uruguay case–control study and the IARC multinational case–control study.

Figure 1.

ORs for cumulative maté consumption in LPDY within categories of mean daily intake in LPD (A < 1.0; B 1.0–1.9; C 2.0–2.9; D ≥ 3.0) and overall (E), and fitted linear models for the EOR using all data (solid line) or restricted data (never and ≥0.5 LPD maté drinkers). Pooled data from the Uruguay case–control study and the IARC multinational case–control study.

Close modal

Effect modification of the association of cumulative maté use

There was significant variation of EOR/LPDY estimates with temperature, years since maté cessation and age at first consumption (P < 0.01; Table 3). The EOR/LPDY estimates increased with temperature, 0.004 (95% CI, −0.002–0.013), 0.007 (95% CI, 0.003–0.013), and 0.016 (95% CI, 0.009–0.027) for warm, hot, and very hot consumers, respectively. In warm maté consumers, ORs by LPDY categories increased monotonically; however, the test of no trend did not reject (P = 0.14). EOR/LPDY estimates varied with years since cessation, 0.009 (95% CI, 0.004–0.015), 0.020 (95% CI, 0.006–0.044), and 0.005 (95% CI, −0.003–0.022) for 0, 1 to 4, and ≥5 years since cessation, respectively, but was not monotonic. Because prodromal symptoms may have influenced consumption, we applied a post hoc categorization <5 and ≥5 years since cessation and found that the EOR/LPDY estimate was greater in current and recent former drinkers, 0.009 (95% CI, 0.004–0.015) than in long-term former drinkers 0.005 (95% CI, −0.003–0.021), with the difference nearly significant (P = 0.08). Subject ages younger than 12 years at first maté consumption exhibited the strongest association, 0.012 (95% CI, 0.006–0.020), compared with older initiators, 0.005 (95% CI, 0.001–0.011) at 12 to 16 years and 0.008 (95% CI, 0.001–0.017) at ≥17 years (P = 0.01).

Table 3.

Pooled data from the Uruguay and IARC multinational case–control studies

ORsa by LPDY  
Modifier1–2930–4950–6970–99≥100EOR/LPDYb95% CIcPd
Temperature 
 Warm 0.88 1.16 1.79 2.11 2.15 0.004 (−0.002–0.013) <0.01 
 Hot 1.56 1.52 1.94 1.46 2.06 0.007 (0.003–0.013)  
 Very hot 0.88 1.56 2.58 2.21 4.56 0.016 (0.009–0.027)  
Years since last maté 
 0 1.27 1.41 1.98 1.74 2.45 0.009 (0.004–0.015) <0.01 
 1–4 2.58 1.76 2.92 1.18 5.07 0.020 (0.006–0.044)  
 ≥5 1.46 2.07 2.00 0.31 2.78 0.005 (−0.003–0.022)  
Age, first maté 
 <12 1.43 1.68 2.28 1.91 3.19 0.012 (0.006–0.020) <0.01 
 12–16 1.20 1.56 1.78 1.13 1.96 0.005 (0.001–0.011)  
 ≥17 1.39 1.14 2.03 2.12 2.47 0.008 (0.001–0.017)  
Sex 
 Males 1.29 1.42 1.96 1.48 2.24 0.007 (0.003–0.013) 0.29 
 Females 1.52 1.55 2.09 2.25 3.64 0.013 (0.004–0.032)  
Attained age 
 <65 1.20 1.64 2.17 2.13 2.92 0.015 (0.007–0.029) 0.14 
 65–74 2.11 2.13 2.86 1.72 2.98 0.006 (0.001–0.015)  
 ≥75 1.20 0.69 1.10 0.97 1.84 0.006 (0.001–0.016)  
Smoking status 
 Never 1.18 1.14 1.73 2.27 4.03 0.018 (0.007–0.038) 0.02 
 Former 1.69 1.15 2.17 1.80 3.03 0.009 (0.002–0.022)  
 Current 1.32 1.78 1.96 1.27 1.69 0.003 (−0.001–0.009)  
Tobacco type (males only) 
 Never 0.89 0.35 1.36 2.06 2.44 0.011 (0.000–0.041) <0.01 
 Blond-only 1.17 1.36 1.96 1.05 0.93 -0.002 (–e–0.005)  
 Mixed/black-only 2.18 2.54 3.28 2.80 4.93 0.014 (0.005–0.032)  
Alcohol status 
 Never 1.74 1.92 2.57 2.68 3.89 0.017 (0.006–0.037) 0.12 
 Former 1.08 1.30 1.29 0.95 1.95 0.004 (−0.001–0.014)  
 Current 1.26 1.27 2.03 1.52 2.22 0.008 (0.002–0.018)  
ORsa by LPDY  
Modifier1–2930–4950–6970–99≥100EOR/LPDYb95% CIcPd
Temperature 
 Warm 0.88 1.16 1.79 2.11 2.15 0.004 (−0.002–0.013) <0.01 
 Hot 1.56 1.52 1.94 1.46 2.06 0.007 (0.003–0.013)  
 Very hot 0.88 1.56 2.58 2.21 4.56 0.016 (0.009–0.027)  
Years since last maté 
 0 1.27 1.41 1.98 1.74 2.45 0.009 (0.004–0.015) <0.01 
 1–4 2.58 1.76 2.92 1.18 5.07 0.020 (0.006–0.044)  
 ≥5 1.46 2.07 2.00 0.31 2.78 0.005 (−0.003–0.022)  
Age, first maté 
 <12 1.43 1.68 2.28 1.91 3.19 0.012 (0.006–0.020) <0.01 
 12–16 1.20 1.56 1.78 1.13 1.96 0.005 (0.001–0.011)  
 ≥17 1.39 1.14 2.03 2.12 2.47 0.008 (0.001–0.017)  
Sex 
 Males 1.29 1.42 1.96 1.48 2.24 0.007 (0.003–0.013) 0.29 
 Females 1.52 1.55 2.09 2.25 3.64 0.013 (0.004–0.032)  
Attained age 
 <65 1.20 1.64 2.17 2.13 2.92 0.015 (0.007–0.029) 0.14 
 65–74 2.11 2.13 2.86 1.72 2.98 0.006 (0.001–0.015)  
 ≥75 1.20 0.69 1.10 0.97 1.84 0.006 (0.001–0.016)  
Smoking status 
 Never 1.18 1.14 1.73 2.27 4.03 0.018 (0.007–0.038) 0.02 
 Former 1.69 1.15 2.17 1.80 3.03 0.009 (0.002–0.022)  
 Current 1.32 1.78 1.96 1.27 1.69 0.003 (−0.001–0.009)  
Tobacco type (males only) 
 Never 0.89 0.35 1.36 2.06 2.44 0.011 (0.000–0.041) <0.01 
 Blond-only 1.17 1.36 1.96 1.05 0.93 -0.002 (–e–0.005)  
 Mixed/black-only 2.18 2.54 3.28 2.80 4.93 0.014 (0.005–0.032)  
Alcohol status 
 Never 1.74 1.92 2.57 2.68 3.89 0.017 (0.006–0.037) 0.12 
 Former 1.08 1.30 1.29 0.95 1.95 0.004 (−0.001–0.014)  
 Current 1.26 1.27 2.03 1.52 2.22 0.008 (0.002–0.018)  

aORs adjusted for study, cigarette smoking (pack-years, cigarettes/d), alcohol consumption (drink-years, mL ethanol/d), age, sex, education, and for Uruguay income and urban/rural residence. Models included a sex-specific fixed offset variable to account for differential effects of maté consumption in urban, never alcohol consumers for the Uruguay data. ORs relative to never maté consumers.

bEstimated EOR/LPDY based on linear ORs for LPDY relative to never-drinkers within levels of a modifier: |$OR(d)\, = \,1 + \sum _i \gamma _i d_i$| for the ith level, where di and γi are the cumulative LPDY and EOR/LPDY within the ith level, respectively. For all data, the EOR/LPDY estimate with 95% CI was 0.009 (0.005–0.14).

cLikelihood-based 95% CI for the EOR/LPDY.

dP value for test of homogeneity of EOR/LPDY across levels of the modifier.

eNot estimable.

The LPDY association was statistically homogeneous by sex (P = 0.29), although category-specific ORs by LPDY were larger in females and EOR/LPDY estimates were 0.013 (95% CI, 0.004–0.032) in females and 0.007 (95% CI, 0.003–0.013) in males. For attained ages younger than 65, 65 to 74, and ≥ 75 years, EOR/LPDY estimates were 0.015 (95% CI, 0.007–0.029), 0.006 (95% CI, 0.001–0.015), and 0.006 (95% CI, 0.001–0.016), respectively, suggesting an enhanced trend at younger ages (P = 0.14). A post hoc categorization of ages younger than 65 and ≥65 years resulted in EOR/LPDY estimates of 0.015 (95% CI, 0.005–0.033) and 0.006 (95% CI, 0.001–0.013), which differed significantly (P = 0.05).

Modification of the EOR/LPDY was inconsistent for smoking related variables. ORs by LPDY varied by cigarette smoking status (P = 0.02), with the strongest association in never-smokers, 0.018 (95% CI, 0.007–0.038), decreasing in former, 0.009 (95% CI, 0.002–0.022), and current-smokers, 0.003 (95% CI, −0.001–0.009). However, ORs at higher LPDY levels drove the variation, as ORs for less than 70 LPDY were similar (Table 3). For less than 70 LPDY, the EOR/LPDY estimates for never, former, and current smokers were 0.006 (95% CI, −0.004–0.023), 0.007 (95% CI, −0.003–0.026), and 0.018 (95% CI, 0.005–0.042), respectively, and homogeneous (P = 0.32). Tobacco type was a significant effect modifier, with trends increased in never-smokers and in mixed/black-only tobacco users, but not in blond tobacco users (P < 0.01). However, for less than 70 LPDY, ORs for blond-only tobacco smokers were elevated and the EOR/LPDY estimate was 0.013 (95% CI, 0.001–0.035), consistent with estimates for never and mixed/black-only tobacco users (P = 0.22).

Category-specific ORs by LPDY were highest in never alcohol drinkers, with EOR/LPDY estimates for never, former, and current alcohol drinkers of 0.017 (95% CI, 0.006–0.037), 0.004 (95% CI, −0.001–0.014), and 0.008 (95% CI, 0.002–0.018), respectively. However, the test of homogeneity of trends was not rejected (P = 0.12). A post hoc evaluation of EOR/LPDY estimates for never and ever alcohol drinkers rejected homogeneity (P = 0.04).

Consistency of results across studies

ORs by LPDY were consistent with linearity among exposed in the Uruguay study (P = 0.91) and among all subjects in the IARC study (P = 0.11), with EOR/LPDY estimates of 0.003 (95% CI, −0.001–0.009) and 0.015 (95% CI, 0.008–0.025), respectively. Homogeneity of EOR/LPDY estimates was rejected (P = 0.01; Supplementary Table SB2).

Adjusted for study differences, variations in EOR/LPDY patterns across the potential modifiers were consistent for the studies, and tests of homogeneity of effect modification did not reject, except for age at first maté consumption (P < 0.01). The EOR/LPDY estimate was largest for ages younger than 12 years in the Uruguay study and for ages 12 to 16 years in the IARC study (Supplementary Table SB2.)

This analysis represents the first detailed assessment of the exposure–response association for maté consumption and ESCC risk and of the potential modifying effects for a broad range of factors. In particular, we evaluated (i) the relationship of ESCC and cumulative maté consumption, (ii) the influence of maté consumption intensity on the strength of association, and (iii) the impact of potential effect modifiers. The pooled results were consistent with the constituent studies (4, 5, 18–22), with marginal ORs increasing significantly with ever use, cumulative intake, and intensity. Our pooled results extended prior analyses to demonstrate that ORs increased linearly with LPDY (Fig. 1), rising to 2.0-fold for ≥100 LPDY consumers. Moreover, maté intensity did not alter the linear association with LPDY, suggesting that the main determinant of risk was cumulative intake and that for a given intake, higher intensity consumption for shorter duration, or lower intensity consumption for longer duration resulted in comparable ORs. We could not however, rule out an enhanced association in low (<0.5 LPD) intensity drinkers, although this enhancement may have reflected differential misclassification, with lower maté intensity cases underreporting cumulative intake.

Epidemiologic studies have linked ESCC to repeated ingestion of high-temperature liquids, such as tea, coffee, and maté (7, 15, 25–27), implicating thermal injury as a carcinogen. Although estimates of the association have varied, increased ORs with beverage temperature are observed in many countries and across diverse beverage types (15). Intraesophageal temperatures are sensitive to initial fluid temperature, time between sips, and sip volume, suggesting substantial inherent variability (28, 29). Moreover, temperatures were self-assessed, further increasing misclassification. Despite the substantial misclassification, the strength of association in the current analysis increased with temperature; EOR/LPDY estimates were 0.004, 0.007, and 0.016 for consumption at warm, hot, and very hot temperatures, respectively (Table 3), consistent with thermal injury damaging the epithelial lining of the esophagus and thereby directly affecting risk or enabling other factors. Experimental animal studies involving high-temperature liquids support this pattern (30–32). Nonetheless, risks for warm maté drinkers remain uncertain. Although category-specific ORs increased monotonically, the test of no trend was not rejected (P = 0.14).

Although there have been relatively few studies and results to date are not conclusive, studies have associated maté consumption with diverse cancer sites, including oral cavity, pharynx, larynx, lung, kidney, and bladder (4–12, 16). Thus, the etiology of ESCC may potentially involve maté-associated nonthermal factors. Attention has focused on PAHs, in particular benzo[a]pyrene, a possible production-acquired contaminate (16, 33), which IARC has classified as a human carcinogen (34, 35). Because cigarette smoke contains PAHs, residual confounding may have influenced maté-related ORs (2, 8). However, substantial confounding in the current analysis seems unlikely because among users the Pearson correlation between LPD of maté and cigarettes/d was small (0.11 in controls), urinary measurements of 1-hydroxypyrene glucuronide, a stable PAH metabolite, correlated positively with maté consumption (14) and, importantly, we observed significant trends in ORs with LPDY in never-smokers and in smokers after extensive smoking adjustment.

Conclusions were not definitive about modification by other maté-related variables. Cessation of maté drinking significantly modified EOR/LPDY estimates (P < 0.01); however, the largest estimate occurred in recent (1–4 years) former drinkers (P = 0.020), with lower estimates in both current (P = 0.009), and long-term (≥5 years) former drinkers (P = 0.005; Table 3). Because prodromal symptoms may have influenced responses, we recalculated EOR/LPDY for less than 5 and ≥5-year cessation and found estimates of 0.009 and 0.006, respectively, indicating reduced maté effects with increased cessation (P < 0.01). This result agreed with two previous studies that found higher ORs in former compared with current drinkers (4, 7), but not another, which found monotonically decreasing ORs with cessation (13). Our analyses were necessarily limited due to few long-term quitters (74 cases and 167 controls). Younger ages at initiation increased the strength of the LPDY association; however, interpretation was problematic because variations in EOR/LPDY estimates were inconsistent across studies (P < 0.01; Supplementary Table SB2).

Cumulative maté effects were statistically homogeneous by sex for each study and the pooled data; however, category-specific ORs with LPDY and EOR/LPDY estimates were greater in females. These results corresponded to previous findings for the IARC study (4). Although not significant, consistency in the enhanced effects in females suggested the need for further evaluation in other study populations.

No definitive conclusions were possible for the roles of age, cigarette smoking and alcohol as effect modifiers. The largest EOR/LPDY estimate occurred for ages <65 years in each study and in the pooled data (Supplementary Table SC2); however, homogeneity of EOR/LPDY estimates was not rejected (P = 0.14). Only under post hoc evaluation did EOR/LPDY estimates vary significantly for ages <65 years. In the pooled data, smoking status and type of tobacco were significant modifiers of the maté association, but higher LPDY consumers drove results. For <70 LPDY (representing 83% of controls), EOR/LPDY estimates were 0.006, 0.007 and 0.018 for never, former and current smokers, respectively, and homogeneous (P = 0.32), which was concordant with a previous result (13). Estimates were −0.002, 0.013, 0.020 in never-smokers, blond-only, mixed/black-only tobacco users (P = 0.22). Finally, although ORs and the EOR/LPDY estimate were greatest in those who never consumed alcohol and homogeneity was not statistically rejected (P = 0.12), the differential EOR/LPDY estimates occurred only in the IARC study (Table 2).

Initial analyses revealed that ORs by LPDY increased linearly in both the IARC and Uruguay datasets, with linearity in the latter dataset occurring only in maté consumers. Although maté-related ORs could vary in populations due to different methods of preparation and consumption, trends with consumption should be roughly comparable. Exploratory analysis of the Uruguay dataset identified a small subgroup of urban residents who never consumed alcohol (4 cases and 114 controls) with significant ORs by ever-consumed maté of 4.2 for males and 13.8 for females. The inclusion of a fixed offset eliminated nonlinearity in the Uruguay data. An alternative approach could have specified a nonlinear relationship for ORs with LPDY in the Uruguay data, and derived an offset for the IARC data that induced a curvilinear pattern to mimic the Uruguay data. We did not apply this approach, as it increases model complexity and because linearity typically represents the preferred first-order approximation (Occam's Razor). A second alternative could have omitted the offset and used a combined linear relationship for the IARC data and a curvilinear relationship for the Uruguay data. Under this approach, the inference in Table 3 was largely unchanged, except EOR/LPDY variations were not significant for attained age (P = 0.87 and P = 0.63 for post hoc categories of ages <65 and ≥65) but were significant for alcohol status (P < 0.01; not shown).

In summary, our results confirmed the hypothesis that drinking maté increases risk of ESCC, with ORs consistent with a linear relationship in cumulative intake. Moreover, the strength of association with cumulative intake was not influenced by consumption intensity, so that greater daily consumption for a shorter duration or less daily consumption for a longer duration resulted in comparable ORs. The increased ORs also occurred at all beverage temperatures, but were greater with higher maté temperatures.

No potential conflicts of interest were disclosed.

Conception and design: J.H. Lubin, C.C. Abnet, P. Boffetta, B.I. Graubard, N. Muñoz, S.M. Dawsey

Development of methodology: J.H. Lubin, G. Acosta, C. Victora, X. Castellsagué

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): E. De Stefani, G. Acosta, P. Boffetta, C. Victora, N. Muñoz, H. Deneo-Pellegrini

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): J.H. Lubin, C.C. Abnet, P. Boffetta, B.I. Graubard, X. Castellsagué

Writing, review, and/or revision of the manuscript: J.H. Lubin, E. De Stefani, C.C. Abnet, G. Acosta, P. Boffetta, C. Victora, B.I. Graubard, N. Muñoz, H. Deneo-Pellegrini, S. Franceschi, X. Castellsagué, A.L. Ronco, S.M. Dawsey

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): X. Castellsagué

This work was supported by the IARC, Lyon, France [Uruguay study; to E. De Stefani, H. Deneo-Pellegrini, A.L. Ronco, and G. Acosta (IARC/CRA ECE/98/17)]. X. Castellsagué, C. Victora, and E. De Stefani, the IARC study and its components were supported with grants from IARC to Fondo de Investigaciones Sanitarias (Spain; FIS 97/0662), Fondo para la Investigacion Cientifica y Tecnologica (Argentina), Institut Municipal d'Investigacio Medica (Barcelona), Fundacao de Amparo a Pesquisa no Estado de Sao Paulo (01/01768-2), and from the European Commission (IC18-CT97-0222), the Comision Honoraria de Lucha contra el Cancer (Montevideo, Uruguay; 5471-066), the International Union Against Cancer, the International Cancer Research Data Bank Program of the National Cancer Institute, and the NIH (Bethesda, MD; N01-CO-65341). J.H. Lubin, C.C. Abnet, B.I. Graubard, and S.M. Dawsey were supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
International Agency for Research on Cancer
. 
IARC monographs on the evaluation of carcinogenic risks to humans (1991)
. 
Volume 51 coffee, tea, mate, methylxanthines, and methylglyoxal
.
Lyon, France
:
IARC
; 
1991
.
2.
Heck
CI
,
De Mejia
E
. 
Yerba Mate tea (Ilex paraguariensis): a comprehensive review on chemistry, health implications, and technological considerations
.
J Food Sci
2007
;
72
:
R138
51
.
3.
Bracesco
N
,
Sanchez
A
,
Contreras
V
,
Menini
T
,
Gugliucci
A
. 
Recent advances on Ilex paraguariensis research: minireview
.
J Ethnopharmacol
2011
;
136
:
378
84
.
4.
Castellsague
X
,
Munoz
N
,
De Stefani
E
,
Victora
CG
,
Castelletto
R
,
Rolon
PA
. 
Influence of mate drinking, hot beverages, and diet on esophageal cancer risk in South America
.
Int J Cancer
2000
;
88
:
658
64
.
5.
De Stefani
E
,
Moore
M
,
Aune
D
,
Deneo-Pellegrini
H
,
Ronco
AL
,
Boffetta
P
, et al
Mate consumption and risk of cancer: a multi-site case–control study in Uruguay
.
Asian Pac J Cancer Prev
2011
;
12
:
1089
93
.
6.
De Stefani
E
,
Fierro
L
,
Mendilaharsu
M
,
Ronco
A
,
Larrinaga
MT
,
Balbi
JC
, et al
Meat intake, “mate” drinking and renal cell cancer in Uruguay: a case–control study
.
Br J Cancer
1998
;
78
:
1239
43
.
7.
Szymanska
K
,
Matos
E
,
Hung
RJ
,
Wuensch-Filho
V
,
Eluf-Neto
J
,
Menezes
A
, et al
Drinking of mate and the risk of cancers of the upper aerodigestive tract in Latin America: a case–control study
.
Cancer Causes Control
2010
;
21
:
1799
806
.
8.
De Stefani
E
,
Boffetta
P
,
Deneo-Pellegrini
H
,
Correa
P
,
Ronco
AL
,
Brennan
P
, et al
Nonalcoholic beverages and risk of bladder cancer in Uruguay
.
BMC Cancer
2007
;
7
:
57
.
9.
Bates
MN
,
Hopenhayn
C
,
Rey
OA
,
Moore
LE
. 
Bladder cancer and mate consumption in Argentina: a case–control study
.
Cancer Lett
2007
;
246
:
268
73
.
10.
De Stefani
E
,
Fierro
L
,
Correa
P
,
Fontham
E
,
Ronco
A
,
Larrinaga
M
, et al
Mate drinking and risk of lung cancer in males: a case–control study from Uruguay
.
Cancer Epidemiol Biomarkers Prev
1996
;
5
:
515
9
.
11.
Dasanayake
AP
,
Silverman
AJ
,
Warnakulasuriya
S
. 
Mate drinking and oral and oro-pharyngeal cancer: a systematic review and meta-analysis
.
Oral Oncology
2010
;
46
:
82
6
.
12.
Goldenberg
D
,
Golz
A
,
Joachims
HZ
. 
The beverage mate: a risk factor for cancer of the head and neck
.
Head Neck
2003
;
25
:
595
601
.
13.
Sewram
V
,
De Stefani
E
,
Brennan
P
,
Boffetta
P
. 
Mate consumption and the risk of squamous cell esophageal cancer in Uruguay
.
Cancer Epidemiol Biomarkers Prev
2003
;
12
:
508
13
.
14.
Fagundes
RB
,
Abnet
CC
,
Strickland
PT
,
Kamangar
F
,
Roth
MJ
,
Taylor
PR
, et al
Higher urine 1-hydroxy pyrene glucuronide (1-OHPG) is associated with tobacco smoke exposure and drinking mate in healthy subjects from Rio Grande do Sul, Brazil
.
BMC Cancer
2006
;
6
:
139
.
15.
Islami
F
,
Boffetta
P
,
Ren
J-S
,
Pedoeim
L
,
Khatib
D
,
Kamangar
F
. 
High-temperature beverages and foods and esophageal cancer risk: a systematic review
.
Int J Cancer
2009
;
125
:
491
524
.
16.
Kamangar
F
,
Schantz
MM
,
Abnet
CC
,
Fagundes
RB
,
Dawsey
SM
. 
High levels of carcinogenic polycyclic aromatic hydrocarbons in mate drinks
.
Cancer Epidemiol Biomarkers Prev
2008
;
17
:
1262
8
.
17.
Kamangar
F
,
Chow
WH
,
Abnet
CC
,
Dawsey
SM
. 
Environmental causes of esophageal cancer
.
Gastroenterol Clin North Am
2009
;
38
:
27
57
.
18.
Castellsague
X
,
Munoz
N
,
De Stefani
E
,
Victora
CG
,
Castelletto
R
,
Rolon
PA
, et al
Independent and joint effects of tobacco smoking and alcohol drinking on the risk of esophageal cancer in men and women
.
Int J Cancer
1999
;
82
:
657
64
.
19.
Castelletto
R
,
Castellsague
X
,
Munoz
N
,
Iscovich
J
,
Chopita
N
,
Jmelnitsky
A
. 
Alcohol, tobacco, diet, mate drinking, and esophageal cancer in Argentina
.
Cancer Epidemiol Biomarkers Prev
1994
;
3
:
557
64
.
20.
Rolon
PA
,
Castellsague
X
,
Benz
M
,
Munoz
N
. 
Hot and cold mate drinking and esophageal cancer in Paraguay
.
Cancer Epidemiol Biomarkers Prev
1995
;
4
:
595
605
.
21.
Victora
CG
,
Munoz
N
,
Day
NE
,
Barcelos
LB
,
Peccin
DA
,
Braga
NM
. 
Hot beverages and esophageal cancer in southern Brazil: a case–control study
.
Int J Cancer
1987
;
39
:
710
6
.
22.
De Stefani
E
,
Munoz
N
,
Esteve
J
,
Vasallo
A
,
Victora
CG
,
Teuchmann
S
. 
Mate drinking, alcohol, tobacco, diet, and esophageal cancer in Uruguay
.
Cancer Res
1990
;
50
:
426
31
.
23.
Breslow
NE
,
Day
NE
. 
Statistical methods in cancer research. The analysis of case–control studies. Vol. I
.
Lyon, France
:
IARC
; 
1980
.
24.
Preston
DL
,
Lubin
JH
,
Pierce
DA
,
McConney
ME
. 
Epicure user's guide
.
Seattle, Washington
:
HiroSoft International Corporation
; 
2006
.
25.
Gao
Y
,
Hu
N
,
Han
XY
,
Ding
T
,
Giffen
C
,
Goldstein
AM
, et al
Risk factors for esophageal and gastric cancers in Shanxi Province, China: a case-control study
.
Cancer Epidemiol
2011
;
35
:
E91
E99
.
26.
Lin
J
,
Zeng
R
,
Cao
W
,
Luo
R
,
Chen
J
,
Lin
Y
. 
Hot beverage and food intake and esophageal cancer in southern China
.
Asian Pac J Cancer Prev
2011
;
12
:
2189
92
.
27.
Islami
F
,
Pourshams
A
,
Nasrollahzadeh
D
,
Kamangar
F
,
Fahimi
S
,
Shakeri
R
, et al
Tea drinking habits and oesophageal cancer in a high risk area in northern Iran: population based case–control study
.
BMJ
2009
;
338
:
b929
.
28.
Dejong
UW
,
Day
NE
,
Mounierk
PL
,
Haguenau
JP
. 
Relationship between ingestion of hot coffee and intraesophageal temperature
.
Gut
1972
;
13
:
24
30
.
29.
Candreva
EC
,
Keszenman
DJ
,
Barrios
E
,
Gelos
U
,
Nunes
E
. 
Mutagenicity induced by hyperthermia, hot mate infusion, and hot caffeine in Saccharomyces-cerevisiae
.
Cancer Res
1993
;
53
:
5750
3
.
30.
Yioris
N
,
Ivankovic
S
,
Lehnert
T
. 
Effect of thermal-injury and oral-administration of N-methyl-N'-nitro-N-nitrosoguanidine on the development of esophageal tumors in Wistar rats
.
Oncology
1984
;
41
:
36
8
.
31.
Li
ZG
,
Shimada
Y
,
Sato
F
,
Maeda
M
,
Itami
A
,
Kaganoi
J
, et al
Promotion effects of hot water on N-nitrosomethylbenzylamine-induced esophageal tumorigenesis in F344 rats
.
Oncol Rep
2003
;
10
:
421
6
.
32.
Tobey
NA
,
Sikka
D
,
Marten
E
,
Caymaz-Bor
C
,
Hosseini
SS
,
Orlando
RC
. 
Effect of heat stress on rabbit esophageal epithelium
.
Am J Physiol
1999
;
276
:
G1322
30
.
33.
Vieira
MA
,
Maraschin
M
,
Rovaris
AA
,
de Mello Castanho
Amboni RD
,
Pagliosa
CM
,
Mendonca
Xavier JJ
, et al
Occurrence of polycyclic aromatic hydrocarbons throughout the processing stages of erva-mate (Ilex paraguariensis)
.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess
2010
;
27
:
776
82
.
34.
Cogliano
VJ
,
Baan
R
,
Straif
K
. 
Updating IARC's carcinogenicity assessment of benzene
.
Am J Ind Med
2011
;
54
:
165
7
.
35.
International Agency for Research on Cancer
. 
IARC monographs on the evaluation of carcinogenic risks to humans (2010)
. 
Volume 92 some non-heterocyclic polycyclic aromatic hydrocarbons and some related exposures
.
Lyon, France
:
IARC
; 
2010
.