Gender and Peripheral Arterial Disease

Article Figures & Data

Table 1.

Characteristics of the Cohort

Demographics and Comorbidities	Total Cohort 403 (100%)	Women 208 (51.6%)	Men 195 (48.4%)	P Value
Age, mean± SE	63.8 ± 0.36	63.4 ± 0.48	64.2 ± 0.55	.33
Ankle-brachial index, mean± SE	1.06 ± 0.01	1.04 ± 0.01	1.08 ± 0.02	.08
Body mass index, mean± SE	30.5 ± 0.36	31.6 ± 0.63	29.8 ± 0.43	.02
Education
<8 years	106 (26.3%)	61 (29.3%)	45 (23.1%)	.03
8–11 years	85 (21.1%)	49 (23.6%)	36 (18.5%)
Graduated from high school	169 (41.9%)	84 (40.4%)	85 (43.6%)
Graduated from college	42 (10.4%)	14 (6.7%)	28 (14.4%)
Diabetes mellitus	153 (37.9%)	74 (35.6%)	79 (40.5%)	.30
Current smoking	76 (18.9%)	29 (13.9%)	47 (24.1%)	.009
Current use of blood pressure medication	267 (66.2%)	128 (61.5%)	139 (71.3%)	.04

Disease Prevalence by Gender and Race	Total Cohort N = 403	PAD N = 67	Non-PAD N = 336	P Value
Women
White	55 (13.6%)	5 (7.5%)	50 (14.9%)
African American	82 (20.3%)	18 (26.9%)	64 (19.0%)	.11
Hispanic^*	71 (17.6%)	10 (14.9%)	61 (18.1%)
Men
White	81 (20.1%)	13 (19.4%)	68 (20.2%)
African American	54 (13.4%)	13 (19.4%)	41 (12.2%)	.29
Hispanic	60 (14.9%)	8 (11.9%)	52 (15.5%)

Table 2.

Characteristics of Patients with PAD

	N (%)		P Value
	Women (n = 33)	Men (n = 34)	P Value
Diabetes mellitus	19 (57.6)	18 (52.9)	>.20
Current smoking	9 (27.3)	11 (32.3)	>.20
Current use of blood pressure medication	29 (87.9)	27 (79.4)	>.20
Hypercholesterolemia	17 (51.5)	13 (38.2)	>.20
Congestive heart failure	2 (6.1)	3 (8.8)	>.20
Atrial fibrillation	7 (21.2)	4 (11.8)	>.20
Rheumatoid arthritis or any arthritis other than rheumatoid	23 (69.7)	18 (52.9)	.16
Stroke or transient ischemic attack	4 (12.1)	3 (8.8)	>.20
Use of at least one nonsteroidal anti-inflammatory agent daily, weekly, or occasionally^*	16 (48.5)	24 (70.6)	.06
Use of pentoxifylline (Trental)	1 (3.0)	0 (0)	>.20
Use of any antiplatelet agent^†	11 (33.3)	15 (44.1)	>.20

* Nonsteroidal anti-inflammatory agents included the following: Ecotrin, Bayer, ibuprofen, Motrin, Aleve, Advil, BC (a powder substance used for pain relief; its ingredients are salicylate, caffeine, and salicylamide), celecoxib, rofecoxib, naproxen, and Alka Seltzer.
† Antiplatelet agents included aspirin, ticlopidine, and clopidogrel.

Table 3.

Prevalence of Leg Symptoms and Mean Walking Impairment Scores

	PAD	Non-PAD	P Value
Women	N = 33	N = 175
No symptoms, n (%)	10 (30.3)	82 (46.9)	.03
Atypical leg symptoms, n (%)	20 (60.6)	90 (51.4)
Intermittent claudication, n (%)	3 (9.1)	3 (1.7)
WIQ subscale, mean (± SD):
Walking distance	N = 32	N = 174	.0004
	29.7 (34.7)	56.8 (39.8)	.0004
Walking speed	N = 32 30.4 (33.6)	N = 173 43.4 (32.2)	.04
Stair climbing	N = 33 33.5 (34.7)	N = 174 45.1 (36.8)	.09
Men	N = 34	N = 161
No symptoms, n (%)	15 (44.1)	84 (52.2)	.16
Atypical leg symptoms, n (%)	17 (50.0)	75 (46.6)
Intermittent claudication, n (%)	2 (5.9)	2 (1.2)
WIQ subscale, mean (± SD):			.33
Walking distance	N = 32 56.8 (41.8)	N = 158 64.3 (38.6)
Walking speed	N = 33 50.2 (39.5)	N = 159 53.7 (34.0)	.61
Stair climbing	N = 33 47.1 (42.6)	N = 158 56.7 (37.4)	.19

Women and Men with PAD only	Women N = 33	Men N = 34	P Value
No symptoms %	10 (30.3)	15 (44.1)	.55
Atypical leg symptoms %	20 (60.6)	17 (50.0)
Intermittent claudication %	3 (9.1)	2 (5.9)
WIQ subscale, mean (± SD):
Walking distance	N = 32 29.7 (34.7)	N = 32 56.8 (41.8)	.006
Walking speed	N = 32 30.4 (33.6)	N = 33 50.2 (39.5)	.03
Stair climbing	N = 33 33.5 (34.7)	N = 33 47.1 (42.6)	.16

Table 4.

Predictors of Peripheral Arterial Disease

Variable	Univariate	Full Model^*		Subset of Full Model^†		Reduced Model^‡
Variable	OR (95% CI)	OR (95% CI)	P Value	OR (95% CI)	P Value	OR (95% CI)	P Value
Gender (women/men)	1.12 (0.66, 1.89)	0.70 (0.34, 1.44)	.33	0.89 (0.49, 1.59)	.69
Education (<High School/ ≥High School)	0.76 (0.45, 1.29)	0.49 (0.21, 1.13)	.09
Currently married (y/n)	0.78 (0.46, 1.32)	1.06 (0.51, 2.24)	.87
Income (<$5000/≥$5000)	1.23 (0.61, 2.48)	0.94 (0.39, 2.27)	.89
Current work status (n/y)	2.06 (1.00, 4.25)	2.52 (0.92, 6.92)	.07			2.67 (1.04, 6.86)	.04
Antiplatelet (y/n)	1.36 (0.79, 2.33)	1.00 (0.47, 2.15)	.99	1.00 (0.55, 1.83)	.99
Arthritis (y/n)	1.16 (0.69, 1.97)	1.13 (0.54, 2.36)	.74	1.09 (0.61, 1.95)	.77
High cholesterol (y/n)	0.97 (0.57, 1.64)	0.90 (0.44, 1.84)	.77	0.89 (0.50, 1.57)	.68
Diabetes (y/n)	2.34 (1.37, 3.98)	3.52 (1.67, 7.41)	.0009	2.64 (1.47, 4.73)	.001	3.42 (1.68, 6.95)	.0007
Hypertension (y/n)	2.32 (1.20, 4.51)	1.27 (0.26, 6.12)	.77	0.64 (0.19, 2.22)	.48
MI (y/n)	1.59 (0.76, 3.30)	1.35 (0.51, 3.55)	.55	1.36 (0.60, 3.05)	.46
Stroke (y/n)	1.98 (0.78, 4.83)	0.80 (0.25, 2.61)	.71	1.64 (0.62, 4.37)	.32
BP medication (y/n)	3.02 (1.52, 5.97)	2.36 (0.54, 10.42)	.26	3.30 (0.94, 11.51)	.06	2.69 (1.14, 6.37)	.02
Current smoker (y/n)	2.13 (1.17, 3.86)	2.63 (1.17, 5.89)	.02	2.83 (1.45, 5.55)	.002	2.37 (1.11, 5.06)	.03
Ever smoker (y/n)	1.77 (1.01, 3.09)
Race
black/white		1.59 (0.67, 3.79)	.30	1.57 (0.79, 3.15)	.20
Latino/white		1.85 (0.62, 5.55)	.27	1.01 (0.47, 2.20)	.98
Age (continuous)		1.03 (0.98, 1.08)	.25	1.03 (0.99, 1.07)	.12
BMI (continuous)		0.93 (0.88, 1.00)	.04			0.94 (0.88, 0.99)	.03

* Full model contains the following variables: gender, education, married, income, current work status, antiplatelet, arthritis, high cholesterol, diabetes, hypertension, myocardial infarction (MI), stroke, blood pressure (BP) medication, current smoker, race (using dummy variables with white as referent), age, and body mass index (BMI). There are missing data for BMI (49 observations), work status (56 observations), and income (24 observations)
† Subset of full model contains the following variables: antiplatelet, arthritis, high cholesterol, diabetes, hypertension, MI, stroke, BP medication, current smoker, race (using dummy variables with white as referent), and age.
‡ Reduced model is built using stepwise procedure with variables having P ≤ .20 entering the model and those with P ≤ .05 remaining in the model. Order of variables entered: diabetes, current smoking, age, current work, age removed, BP medication entered, BMI entered, education entered, and then education removed.

Table 5.

Comparisons by Gender and PAD Status of SF-36 Quality of Life Scores