Association between alcohol consumption and rotator cuff tear

Figures & data

Table 1. Baseline characteristics of patients

Cases	249
Tear type:
Small	94
Large	88
Massive	67
Controls	356
Sex, M/F	325/280	p = 0.08
Mean age (range), years
Cases	64 (54-78)
Controls	66 (58-82)	p = 0.2
BMI
Men	23 (18-25)
Women	23 (19-24)	p = 0.2

Table 2. Mean values (range) of history of alcohol intake: total alcohol intake, and wine, beer, and liquor intake in cases and controls, according to sex

	Women	p-value	Men	p-value
Years of alcohol intake
Cases	31 (14-45)		35 (18-58)
Controls	26 (15-40)	0.02	29 (17-42)	0.04
Total ethanol intakea
Cases	15 (3-38)		29 (3-40)
Controls	13 (2-36)	0.04	25 (3-39)	0.03
Ethanol from wine^a
Cases	9.9 (1-22)		24 (0-32)
Controls	7.8 (0-18)	0.04	20 (0-28)	< 0.001
Ethanol from beer^a
Cases	2.9 (0-6)		6.2 (0-12)
Controls	2.5 (0-7)	0.5	4.4 (0-9)	0.03
Ethanol from liquor^a
Cases	0.9 (0-2)		0.8 (0-2.1)
Controls	0.7 (0-2.5)	0.6	0.8 (0-2)	0.7

a in g per day.

Table 5. Logistic regression analysis of age, sex alcohol intake, smoking, and diabetes mellitus and odds ratios (ORs) with 95% CI

	Cases (n = 249)	Controls (n = 356)	OR	95% CI	p-value
Age (range), years	64 (54-78)	66 (58-82)	0.97	(0.76-1.2)	0.008
Sex, M/F	139/110	186/170	0.36	(0.15-0.66)	0.06
Alcohol intake (range)^a	23 (3-40)	19 (2-39)	1.2	(0.88-2.3)	0.002
Smoking (never/current/former)	102/108/39	176/129/51	1.1	(0.65-2.9)	0.03
Diabetes mellitus (presence/absence)	93/156	122/234	4.4	(1.6-5.2)	< 0.001

a in g per day