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. 2021 Feb 2;79(4):gbab019. doi: 10.1093/geronb/gbab019

Table 3.

Results From Multilevel Models on the Effects of MCI Status on Features of Daily Social Interactions

Predictor: MCI status
Model 1 (unadjusted) Model 2 (adjusted)
Outcomes b OR SE p 95% CI b OR SE p 95% CI
Any daily social interactions −0.12 0.89 0.05 .012 [−0.22, −0.03] −0.08 0.92 0.05 .104 [−0.17, 0.02]
Positive daily social interactions −0.15 0.86 0.05 .004 [−0.26, −0.05] −0.13 0.88 0.05 .013 [−0.24, −0.03]
Negative daily social interactionsa −0.23 0.79 0.29 .427 [−0.81, 0.35] −0.14 0.87 0.31 .661 [−0.74, 0.47]
Diversity of daily interaction partners 0.02 1.02 0.04 .527 [−0.05, 0.09] 0.04 1.04 0.03 .286 [−0.03, 0.11]
Daily in-person socializing −0.37 0.69 0.12 .001 [−0.59, −0.14] −0.26 0.77 0.11 .020 [−0.48, −0.04]
Daily online socializing −0.58 0.56 0.33 .076 [−1.22, 0.06] −0.44 0.64 0.33 .175 [−1.09, 0.20]

Notes: 95% CI = 95% confidence interval for estimates; MCI = mild cognitive impairment; OR = odds ratio. N = 311 persons, 4,245 observations used in multilevel modeling models. MCI status: 1 = MCI, 0 = non-MCI. Model 1 is the model without any covariates; Model 2 included sex, age, race/ethnicity, education (years), employment, marital status, and living status as covariates. Poisson estimate was used for count outcomes.

aLogistic estimate was used for the binary outcome (predicting the probability of 1 = any negative social interactions that day vs no negative social interactions).