Is there an association between ageist attitudes and frailty?

BMC Geriatrics

Table 1 Participant Characteristics Stratified by Frailty status

	Total (n = 381, 100%)	Robust (n = 42, 11.02%)	Prefrail (n = 227, 59.58%)	Frail (n = 112, 29.40%)	P
Age, mean (SD)	60.51 (7.16)	59.14 (7.31)	60.59 (7.40)	60.84 (6.60)	.408
Gender, n (%)	342 (89.76)	38 (90.48)	202 (88.99)	102 (91.07)	.827
Caucasian, n (%)	183 (48.03)	17 (40.48)	111 (48.90)	55 (49.11)	.583
Not Hispanic*, n (%)	335 (87.93)	34 (80.95)	199 (87.67)	102 (91.07)	.225
Married, n (%)	91 (23.90)	24 (57.10)^b	51 (22.50)^a	16 (14.30)^b	<.0001
Median Household Income, mean $ (SD)	45,942 (18,375)	48,549 (19,226)	45,799 (18,562)	45,256 (17,742)	.603
Charlson Comorbidity Index, mean (SD)	3.80 (1.87)	2.74 (1.32)^a	3.61 (1.70)^b	4.56 (2.11)^c	<.0005
More than 5 Medications, n (%)	195 (51.18)	3 (7.14)^a	104 (45.81)^b	88 (78.57)^c	<.0005
Frailty Index, mean (SD)	.18 (.071)	.07 (.02)^a	.16 (.03)^b	.27 (.05)^c	<.0005
Kogan Scores, mean (SD)	121.13 (11.90)	123.36 (12.52)	120.89 (13.13)	120.76 (8.59)	.457
IAT Scores*, mean (SD)	.6208 (.4746)	.6754 (.4575)	.6302 (.4606)	.58349 (.5091)	.744

SD standard deviation, n number of participants
*Available for 339 participants
Data with different superscript letters are significantly different p < 0.05, according to the post hoc ANOVA statistical analysis for continuous variables and chi square for categorical variables. The column means test table assigns a superscript letter (a, b or c) to the robust, prefrail and frail groups. If a pair of values is significantly different, the values have different subscript letters assigned to them. If a pair of values are not significantly different, the values will have the same superscript letters assigned to them. Data without superscripts is not significantly different between robust, prefrail and frail groups

ISSN: 1471-2318