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The first was adjusted only for age and sex.
The first was adjusted for sex and race/ethnicity.
First, we carried out our analyses using two multivariable models: the first was adjusted for age, race/ethnicity, PIR, tobacco smoking, alcohol consumption, and vigorous physical activity.
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The eyepiece must first be adjusted before any adjustment of the objective.
Two sets of multivariable models were estimated, the first were adjusted for these covariates and the second set also included mutual adjustment for each of the other insulin-related biomarkers being assessed here.
Models were fitted to the complete fMRI time series, with data for each condition first being adjusted for the general linear model's fit to all other conditions.
The second was adjusted for sex, race/ethnicity, education, smoking status, BMI, systolic blood pressure, and HDL cholesterol.
The first model was unadjusted, the second was adjusted for age and gender but not eGFR, and the third model was adjusted for age, gender, body mass index (BMI), MEQ, BDI-II, energy intake, smoking pattern, alcohol consumption and IPAQ.
The second is adjusting the training data at the appropriate time on the basis of the performance of the proposed network on the validation set.
The first model was adjusted for demographics, the second included adjustment for socioeconomic factors and the third for medical and substance abuse comorbidities.
The first model was adjusted for sex and age; the second included additional adjustment for education, ethnicity, and co-habitation; and the third also included adjustment for comorbidity.
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