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. 2009 Mar 26;338:b929. doi: 10.1136/bmj.b929

Table 2.

Distribution of usual tea drinking habits and corresponding odds ratios (95% CIs) among 300 cases with oesophageal squamous cell carcinoma and 571 matched controls, in Golestan, northern Iran, 2003-7. Values are numbers (percentages) of participants unless stated otherwise

Variables Cases (n=300) Controls (n=571) Crude odds ratio (95% CI) Adjusted odds ratio* (95% CI) P value for trend†
Tea temperature:
Warm or lukewarm 127 (42.6) 394 (69.4) 1.00 1.00 <0.001
Hot 108 (36.2) 155 (27.3) 2.14 (1.52 to 3.01) 2.07 (1.28 to 3.35)
Very hot 63 (21.1) 19 (3.3) 9.33 (5.26 to 16.56) 8.16 (3.93 to 16.91)
Interval between tea being poured and drunk (minutes):
≥4 132 (44.3) 394 (69.5) 1.00 1.00 <0.001
2-3 112 (37.6) 138 (24.3) 2.32 (1.68 to 3.23) 2.49 (1.62 to 3.83)
<2 54 (18.1) 35 (6.2) 4.03 (2.50 to 6.49) 5.41 (2.63 to 11.14)
Amount of black tea consumed (ml/day):
0-675 48 (18.0) 81 (21.0) 1.00 1.00 0.03
676-920 40 (15.0) 75 (19.5) 0.85 (0.46 to 1.58) 0.91 (0.43 to 1.91)
921-1215 37 (13.9) 86 (22.3) 0.68 (0.38 to 1.23) 0.68 (0.34 to 1.37)
1216-1725 65 (24.3) 70 (18.2) 1.57 (0.89 to 2.75) 1.46 (0.75 to 2.86)
≥1726 77 (28.8) 73 (19.0) 1.86 (1.07 to 3.23) 1.83 (0.93 to 3.59)
Frequency of green tea consumption:
Never, <weekly 249 (93.6) 356 (92.2) 1.00 1.00 0.82
Daily, weekly 17 (6.4) 30 (7.8) 0.65 (0.32 to 1.31) 0.89 (0.38 to 2.09)

Because of missing data and one participant who did not drink tea, number of cases and controls for some variables may be less than 300 and 571, respectively.

*Adjusted for ethnicity (non-Turkmen or Turkmen), daily vegetable intake (logarithmic scale), alcohol consumption (never or ever), tobacco or opium ever use (none, only tobacco, only opium, or both), duration of residence in rural areas (0, 1-20 years, or >20 years), education level (no school, primary school, or middle school or higher), car ownership (no or yes), and variables listed in table, excluding interval variable; interval variable was not adjusted for tea temperature.

†P values come from adjusted conditional logistic regression models in which consecutive integers were assigned to consecutive categories of each variable.