Sentences with phrase «multivariable analyses for»

The results from the longitudinal multivariable analyses for GI and glycemic load on the basis of available carbohydrate are shown in Table 4.

Not exact matches

In multivariable analysis, compared to women in the lowest quartile of whole body fat mass, women in the highest quartile had approximately a doubling in the risk for ER - positive breast cancer.

In all multivariable analyses, we included all of the covariates already described plus the conception season (winter, fall, spring, and summer) to control for influenza infection and vaccination seasonality.

In the multivariable analysis, we further adjusted for several potential dietary and lifestyle confounding factors, including multivitamin use, smoking status, pack - years of smoking, body mass index, physical activity, alcohol consumption, history of hypertension diagnosis, glycemic index, and intake of whole grains, total fiber, fruits, and vegetables.

Multivariable analysis indicated that age, sex, health status, and cat lifestyle and source were significantly associated with risk of seropositivity, with adults more likely to be seropositive than juveniles (adjusted odds ratios [ORs], 2.5 and 2.05 for FeLV and FIV seropositivity, respectively), sexually intact adult males more likely to be seropositive than sexually intact adult females (adjusted ORs, 2.4 and 4.66), and outdoor cats that were sick at the time of testing more likely to be seropositive than healthy indoor cats (adjusted ORs, 8.89 and 11.3).

Other risk factors were assessed and adjusted for by multivariable logistic regression analyses.

aChild Behavior Checklist for 4 - 18 years; bChildren who are currently visiting their father who used to perpetrate intimate partner violence and already separated from their mothers; cInternalizing problems = Withdrawn + Somatic complaints + Anxious / depressed; dExternalizing problems = Delinquent behavior + Aggressive behavior; Total problems = the sum of the scores of all the nine subscales of the CBCL; eAdjusted odds ratios calculated by multivariable logistic regression analysis; fThe dependent variable: 0 = non - clinical, 1 = clinical; gp values calculated by multivariable logistic regression analysis; hStandardized regression coefficients calculated by multivariable regression analysis; ip values calculated by multivariable regression analysis; jVariance Inflation Factor; k0 = non-visiting, 1 = visiting; lThe score of the subscale (anxiety) of the Hospital Anxiety and Depression Scale; mThe score of the subscale (depression) of the Hospital Anxiety and Depression Scale; nThe number of years the child lived with the father in the past; oAdjusted R2 calculated by multivariable regression analysis.

Other strengths of our analysis include its large nationally representative and diverse sample, as well as the rich availability of covariates for inclusion in multivariable models.

With daily media use at 2 years as our outcome, we conducted weighted multivariable regression analyses, controlling for child, maternal, and household characteristics.

Generalized estimating equations extension of multivariable linear regression analyses for repeated measures examined predictors of general and specific adherence.

As in the univariate analyses, the decreases in total, physical, and social PedsQL scores with increasing weight category remained significant for responses from both children and parent - proxies even after multivariable adjustment.

As a result, and together with incomplete data in some variables across subjects, the sample sizes for variables in the bivariate and multivariable analyses were less than those for the completed number of cross-sectional and registration - linked ACE score profiles.

Significant independent variables (p - value < 0.2) were considered for multivariable analysis.

Binary logistic regression was employed for multivariable analysis, as the dependent variable was dichotomous.

Multivariable analyses were used to assess group differences in outcomes, controlling for baseline measures.

Indeed, it seems unreasonable to expect that volunteers would successfully identify adolescents with depressive symptoms when professionals so often fail to.37, 38 Our findings of continued poor mental health and possibly increased support need by participants could be explained by bias from differential dropout rates, although this was controlled for in the multivariable analysis.