Tablas

Esta primera tabla es para mostrar las caracteristicas de los sujetos

Table 1. Demographics features
Characteristic N = 791
Sex
H 30 (38%)
M 49 (62%)
Age 68.1 (6.5)
Dexterity
Diestro 75 (95%)
Zurdo 3 (3.8%)
Zurdo Contrariado 1 (1.3%)
Education (years) 15.91 (2.28)
Unknown 11
CAIDE total score 7.55 (2.04)
Unknown 2
MIND diet score 8.04 (1.48)
IPAQ classification
Active 45 (57%)
Inactive 2 (2.5%)
Minimally active 32 (41%)
First degree relatives w/ cognitive impairment 45 (57%)
HADS anxiety (raw score) 8.1 (4.0)
Unknown 36
HADS depression (raw score) 5.0 (3.4)
Unknown 36
1 n (%); Mean (SD)

Risk factors

Esta tabla resume los factores de riesgo presentes en los individuos cuando se presento a la consulta

Table 2. Risk factors features
Characteristic Overall, N = 791 H, N = 301 M, N = 491 p-value2
CAIDE total score 7.55 (2.04) 8.07 (2.07) 7.21 (1.97) 0.077
Education 0.3
>10 years 76 (96%) 30 (100%) 46 (94%)
7-9 years 3 (3.8%) 0 (0%) 3 (6.1%)
<7 years 0 (0%) 0 (0%) 0 (0%)
Hypertension 29 (37%) 12 (40%) 17 (35%) 0.6
Body mass index >0.9
>30 kg/m2 40 (51%) 15 (50%) 25 (51%)
<30 kg/m2 39 (49%) 15 (50%) 24 (49%)
Dyslipidemia 33 (43%) 12 (40%) 21 (45%) 0.8
Physical activity 39 (49%) 13 (43%) 26 (53%) 0.5
First degree relatives w/ cognitive impairment 45 (57%) 19 (63%) 26 (53%) 0.5
Social isolation 20 (25%) 2 (6.7%) 18 (37%) 0.003
1 Mean (SD); n (%)
2 Welch Two Sample t-test; Fisher's exact test

Lifestyle changes

Esta tabla resume lo que serian los cmabios que los individuos emprendieron despues d ela consulta

Table 3. Changes in lifestyle
Characteristic Overall, N = 791 H, N = 301 M, N = 491 p-value2
CAIDE total score 7.55 (2.04) 8.07 (2.07) 7.21 (1.97) 0.077
cut back on heavy drinking of alcohol in the past 3 months? 0.13
I do not drink heavily 62 (78%) 20 (67%) 42 (86%)
No 5 (6.3%) 3 (10%) 2 (4.1%)
Yes 12 (15%) 7 (23%) 5 (10%)
cut back on smoking in the past 3 months? >0.9
I do not smoke 72 (91%) 28 (93%) 44 (90%)
No 3 (3.8%) 1 (3.3%) 2 (4.1%)
Yes 4 (5.1%) 1 (3.3%) 3 (6.1%)
exercised at least 3-4 times a week over the past 3 months? 29 (37%) 14 (47%) 15 (31%) 0.2
healthy diet regularly over the past 3 months? 52 (66%) 20 (67%) 32 (65%) >0.9
IPAQ total METS (minutes/week) 2,967 (2,234) 3,282 (2,362) 2,775 (2,154) 0.3
IPAQ classification 0.035
Active 45 (57%) 20 (67%) 25 (51%)
Inactive 2 (2.5%) 2 (6.7%) 0 (0%)
Minimally active 32 (41%) 8 (27%) 24 (49%)
MIND diet score 8.04 (1.48) 7.48 (1.63) 8.39 (1.28) 0.012
1 Mean (SD); n (%)
2 Welch Two Sample t-test; Fisher's exact test

Network characteristics

Reproducimos la tabla del paper

## Warning for variable 'network_size':
## simpleWarning in wilcox.test.default(x = c(6, 18, 11, 8, 9, 6, 2, 8, 4, 6, 7, : cannot compute exact p-value with ties
## Warning for variable 'density':
## simpleWarning in wilcox.test.default(x = c(1, 0.722222222222222, 1, 0.392857142857143, : cannot compute exact p-value with ties
## Warning for variable 'constraint':
## simpleWarning in wilcox.test.default(x = c(64.8, 37.8874054762437, 64.8, 39.0086493078144, : cannot compute exact p-value with ties
## Warning for variable 'effsize':
## simpleWarning in wilcox.test.default(x = c(1, 4.11111111111111, 1, 6.03571428571429, : cannot compute exact p-value with ties
## Warning for variable 'max_degree':
## simpleWarning in wilcox.test.default(x = c(4, 8, 4, 7, 8, 5, 1, 4, 3, 5, 4, 4, : cannot compute exact p-value with ties
## Warning for variable 'mean_degree':
## simpleWarning in wilcox.test.default(x = c(4, 5.77777777777778, 4, 2.75, 6, 5, : cannot compute exact p-value with ties
## Warning for variable 'kin_prop':
## simpleWarning in wilcox.test.default(x = c(1, 0.333333333333333, 1, 0.375, 0.555555555555556, : cannot compute exact p-value with ties
## Warning for variable 'age_sd':
## simpleWarning in wilcox.test.default(x = c(18.132843130629, 4.13655788199695, : cannot compute exact p-value with ties
## Warning for variable 'IQVsex':
## simpleWarning in wilcox.test.default(x = c(0.64, 0.987654320987654, 0.96, 0.75, : cannot compute exact p-value with ties
## Warning for variable 'weak_freq_prop':
## simpleWarning in wilcox.test.default(x = c(0, 0.444444444444444, 0, 0.625, 0.222222222222222, : cannot compute exact p-value with ties
## Warning for variable 'weak_dur_prop':
## simpleWarning in wilcox.test.default(x = c(0, 0, 0, 0.25, 0, 0, 0, 0, 0.25, 0, : cannot compute exact p-value with ties
## Warning for variable 'far_dist_prop':
## simpleWarning in wilcox.test.default(x = c(0.4, 0.222222222222222, 0, 0.75, 0, : cannot compute exact p-value with ties
## Warning for variable 'smoking_prop':
## simpleWarning in wilcox.test.default(x = c(0, 0.222222222222222, 0.2, 0, 0, 0, : cannot compute exact p-value with ties
## Warning for variable 'no_exercise_prop':
## simpleWarning in wilcox.test.default(x = c(0.4, 0.555555555555556, 0.6, 0.375, : cannot compute exact p-value with ties
## Warning for variable 'drinking_prop':
## simpleWarning in wilcox.test.default(x = c(0, 0, 0.2, 0, 0, 0, 0, 0, 0, 0.166666666666667, : cannot compute exact p-value with ties
## Warning for variable 'bad_diet_prop':
## simpleWarning in wilcox.test.default(x = c(0.2, 0.222222222222222, 0.4, 0.25, : cannot compute exact p-value with ties
Characteristic Overall, N = 791 H, N = 301 M, N = 491 p-value2
Network structure
Size 8.0 (5.0, 12.0) 7.0 (4.2, 10.5) 9.0 (5.0, 12.0) 0.078
Density 0.86 (0.61, 1.00) 0.85 (0.67, 1.00) 0.86 (0.47, 1.00) 0.3
Constraint 46 (36, 62) 52 (40, 69) 45 (36, 56) 0.042
Effective size 2.52 (1.26, 4.57) 2.17 (1.25, 4.14) 2.67 (1.66, 5.14) 0.3
Unknown 1 0 1
Maximum degre 5.00 (4.00, 7.50) 5.00 (3.25, 7.75) 5.00 (4.00, 7.00) 0.7
Mean degree 4.00 (2.67, 5.79) 4.00 (2.76, 5.69) 4.00 (2.67, 5.80) 0.8
Network composition
Percent kin 0.50 (0.30, 0.67) 0.50 (0.34, 0.73) 0.40 (0.20, 0.67) 0.14
Standard deviation of age 12.7 (8.2, 16.3) 11.9 (5.9, 16.2) 14.0 (10.4, 16.4) 0.2
Diversity of sex (IQV) 0.75 (0.44, 0.96) 0.89 (0.75, 0.97) 0.64 (0.36, 0.89) 0.007
Percent contacted weekly or less often 0.00 (0.00, 0.20) 0.00 (0.00, 0.19) 0.00 (0.00, 0.20) 0.4
Percent who have been known for less than 6 years 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) 0.00 (0.00, 0.11) 0.2
Percent who live more than 15 miles away 0.22 (0.00, 0.40) 0.24 (0.00, 0.44) 0.20 (0.10, 0.33) 0.7
Network composition / Health habits
Percent who smoke 0.00 (0.00, 0.17) 0.00 (0.00, 0.24) 0.00 (0.00, 0.13) 0.3
Percent who do not exercise 0.50 (0.20, 0.60) 0.50 (0.26, 0.67) 0.43 (0.20, 0.57) 0.4
Percent who heavy drink 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) 0.6
Percent who have a unhealthy diet 0.20 (0.00, 0.44) 0.17 (0.00, 0.38) 0.20 (0.00, 0.50) 0.3
1 Median (IQR)
2 Wilcoxon rank sum test

Model to predict Physical exercise

Este modelo predice la intensidad de METS que los individuos haran

Characteristic Beta 95% CI1 p-value
Size 104 -79, 286 0.3
Sex
H — —
M -1,110 -2,252, 32 0.061
Constraint -25 -78, 28 0.4
Effective size -387 -871, 96 0.12
Diversity of sex (IQV) -638 -2,138, 863 0.4
Standard deviation of age 15 -77, 108 0.7
Mean degree -72 -470, 326 0.7
Percent who do not exercise -2,825 -4,723, -927 0.005
Percent who heavy drink 536 -2,096, 3,168 0.7
Percent who have a unhealthy diet 981 -876, 2,839 0.3
1 CI = Confidence Interval

Este es el reporte del modelo para pasarlo al paper solo pongamos lo representativo

## We fitted a linear model (estimated using ML) to predict ipaq_total_mets with network_size, Sexo, constraint, effsize, IQVsex, age_sd, mean_degree, no_exercise_prop, drinking_prop and bad_diet_prop (formula: ipaq_total_mets ~ network_size + Sexo + constraint + effsize + IQVsex + age_sd + mean_degree + no_exercise_prop + drinking_prop + no_exercise_prop + bad_diet_prop). The model's explanatory power is moderate (R2 = 0.21). The model's intercept, corresponding to network_size = 0, Sexo = H, constraint = 0, effsize = 0, IQVsex = 0, age_sd = 0, mean_degree = 0, no_exercise_prop = 0, drinking_prop = 0 and bad_diet_prop = 0, is at 6676.79 (95% CI [905.44, 12448.15], t(67) = 2.27, p = 0.023). Within this model:
## 
##   - The effect of network size is statistically non-significant and positive (beta = 103.75, 95% CI [-78.50, 286.01], t(67) = 1.12, p = 0.265; Std. beta = 0.20, 95% CI [-0.15, 0.55])
##   - The effect of Sexo [M] is statistically non-significant and negative (beta = -1109.89, 95% CI [-2251.74, 31.97], t(67) = -1.91, p = 0.057; Std. beta = -0.49, 95% CI [-1.00, 0.01])
##   - The effect of constraint is statistically non-significant and negative (beta = -25.04, 95% CI [-78.26, 28.18], t(67) = -0.92, p = 0.356; Std. beta = -0.23, 95% CI [-0.71, 0.26])
##   - The effect of effsize is statistically non-significant and negative (beta = -387.46, 95% CI [-871.08, 96.15], t(67) = -1.57, p = 0.116; Std. beta = -0.33, 95% CI [-0.74, 0.08])
##   - The effect of IQVsex is statistically non-significant and negative (beta = -637.57, 95% CI [-2138.18, 863.04], t(67) = -0.83, p = 0.405; Std. beta = -0.10, 95% CI [-0.34, 0.14])
##   - The effect of age sd is statistically non-significant and positive (beta = 15.28, 95% CI [-77.40, 107.96], t(67) = 0.32, p = 0.747; Std. beta = 0.04, 95% CI [-0.20, 0.27])
##   - The effect of mean degree is statistically non-significant and negative (beta = -72.27, 95% CI [-470.47, 325.93], t(67) = -0.36, p = 0.722; Std. beta = -0.07, 95% CI [-0.46, 0.32])
##   - The effect of no exercise prop is statistically significant and negative (beta = -2824.97, 95% CI [-4722.80, -927.14], t(67) = -2.92, p = 0.004; Std. beta = -0.34, 95% CI [-0.57, -0.11])
##   - The effect of drinking prop is statistically non-significant and positive (beta = 536.23, 95% CI [-2096.04, 3168.50], t(67) = 0.40, p = 0.690; Std. beta = 0.05, 95% CI [-0.18, 0.27])
##   - The effect of bad diet prop is statistically non-significant and positive (beta = 981.50, 95% CI [-876.44, 2839.43], t(67) = 1.04, p = 0.300; Std. beta = 0.13, 95% CI [-0.12, 0.38])
## 
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using

Model to predict adherence to mediteranean diet

Este modelo predice el MIND score de los individuos

Characteristic Beta 95% CI1 p-value
Size -0.03 -0.14, 0.09 0.6
Sex
H — —
M 0.53 -0.20, 1.3 0.2
Constraint -0.01 -0.04, 0.02 0.5
Effective size 0.10 -0.21, 0.41 0.5
Diversity of sex (IQV) -0.55 -1.5, 0.41 0.3
Standard deviation of age 0.03 -0.03, 0.09 0.3
Mean degree -0.11 -0.36, 0.14 0.4
Percent who do not exercise -1.2 -2.4, -0.02 0.051
Percent who heavy drink 0.53 -1.1, 2.2 0.5
Percent who have a unhealthy diet 0.73 -0.46, 1.9 0.2
1 CI = Confidence Interval 

## We fitted a linear model (estimated using ML) to predict mind_score with network_size, Sexo, constraint, effsize, IQVsex, age_sd, mean_degree, no_exercise_prop, drinking_prop and bad_diet_prop (formula: mind_score ~ network_size + Sexo + constraint + effsize + IQVsex + age_sd + mean_degree + no_exercise_prop + drinking_prop + no_exercise_prop + bad_diet_prop). The model's explanatory power is moderate (R2 = 0.24). The model's intercept, corresponding to network_size = 0, Sexo = H, constraint = 0, effsize = 0, IQVsex = 0, age_sd = 0, mean_degree = 0, no_exercise_prop = 0, drinking_prop = 0 and bad_diet_prop = 0, is at 8.92 (95% CI [5.24, 12.61], t(67) = 4.75, p < .001). Within this model:
## 
##   - The effect of network size is statistically non-significant and negative (beta = -0.03, 95% CI [-0.14, 0.09], t(67) = -0.46, p = 0.643; Std. beta = -0.08, 95% CI [-0.42, 0.26])
##   - The effect of Sexo [M] is statistically non-significant and positive (beta = 0.53, 95% CI [-0.20, 1.26], t(67) = 1.42, p = 0.157; Std. beta = 0.36, 95% CI [-0.14, 0.85])
##   - The effect of constraint is statistically non-significant and negative (beta = -0.01, 95% CI [-0.04, 0.02], t(67) = -0.63, p = 0.531; Std. beta = -0.15, 95% CI [-0.62, 0.32])
##   - The effect of effsize is statistically non-significant and positive (beta = 0.10, 95% CI [-0.21, 0.41], t(67) = 0.61, p = 0.540; Std. beta = 0.12, 95% CI [-0.27, 0.52])
##   - The effect of IQVsex is statistically non-significant and negative (beta = -0.55, 95% CI [-1.51, 0.41], t(67) = -1.12, p = 0.264; Std. beta = -0.13, 95% CI [-0.36, 0.10])
##   - The effect of age sd is statistically non-significant and positive (beta = 0.03, 95% CI [-0.03, 0.09], t(67) = 1.11, p = 0.265; Std. beta = 0.13, 95% CI [-0.10, 0.36])
##   - The effect of mean degree is statistically non-significant and negative (beta = -0.11, 95% CI [-0.36, 0.14], t(67) = -0.84, p = 0.400; Std. beta = -0.16, 95% CI [-0.55, 0.22])
##   - The effect of no exercise prop is statistically significant and negative (beta = -1.23, 95% CI [-2.44, -0.02], t(67) = -1.99, p = 0.047; Std. beta = -0.23, 95% CI [-0.45, -3.03e-03])
##   - The effect of drinking prop is statistically non-significant and positive (beta = 0.53, 95% CI [-1.15, 2.22], t(67) = 0.62, p = 0.533; Std. beta = 0.07, 95% CI [-0.15, 0.29])
##   - The effect of bad diet prop is statistically non-significant and positive (beta = 0.73, 95% CI [-0.46, 1.92], t(67) = 1.21, p = 0.228; Std. beta = 0.15, 95% CI [-0.09, 0.39])
## 
## Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using