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. 2020 Oct 27;20:427. doi: 10.1186/s12877-020-01820-4

Table 1.

Baseline sample sociodemographic characteristics (2017) of Prospective GERiatric Observational (ProGERO) Study, according to the 10-min Target Geriatric Assessment (10-TaGA) risk categories (n = 1336)

Sociodemographic characteristics 10-TaGA risk categories
Total Low (n = 160) Medium (n = 735) High (n = 441) P-value
Age (years), mean (SD) 82.22 (7.58) 78.74 (7.67) 82.35 (7.34) 83.26 (7.59) < 0.001
Female, n (%) 938 (70.21) 97 (60.62) 520 (70.75) 321 (72.79) 0.014
Ethnicity, n (%)
White 758 (56.74) 100 (62.50) 415 (56.46) 243 (55.10) 0.488
Black 376 (28.14) 17 (10.62) 85 (11.56) 51 (11.57)
Mixed 153 (11.45) 35 (21.88) 207 (28.17) 134 (30.39)
Asian 45 (3.37) 8 (5.00) 26 (3.54) 11 (2.49)
Indigenous 4 (0.30) 0 (0.00) 2 (0.27) 2 (0.45)
Marital status, n (%)
Widowed 698 (52.25) 57 (35.62) 391 (53.20) 250 (56.69) < 0.001
Married 457 (34.21) 83 (51.87) 249 (33.88) 125 (28.34)
Single 92 (6.89) 11 (6.88) 42 (6.12) 36 (8.16)
Divorced 89 (6.66) 9 (5.53) 50 (6.80) 30 (6.81)
Level of literacy (years), median (IQR) 4 (1–5) 4 (3–10) 4 (2–5) 4 (1–4) < 0.001
Annual household income per capitaa, n (%) (N = 1318)
<  4000 USD 345 (26.18) 38 (24.36) 191 (26.27) 116 (26.67) 0.028
4000–8000 USD 684 (51.90) 75 (48.08) 364 (50.07) 245 (56.32)
>  8000 USD 289 (21.92) 43 (27.56) 172 (23.66) 74 (17.01)

aannual household income was classified according to the Brazilian minimum wage in 2017 (1 minimal wage = 4000 USD per year)

10-TaGA 10-min Target Geriatric Assessment, SD standard deviation, IQR interquartile range, USD United States dollar

To compare the 10-TaGA risk categories, we used one-way analysis of variance (ANOVA), its non-parametric equivalent (Kruskal-Wallis), and the trend chi-square test. All statistical tests were two-tailed, and an alpha level of 0.05 was used to determine significance