Exemplos de uso de Socioeconomic variable em Inglês e suas traduções para o Português
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
The socioeconomic variables of the studied population are.
Initially, the association between the contextual socioeconomic variable and the outcome of interest was tested.
The socioeconomic variables included the following data.
Inverse association was also observed mostly when income was the socioeconomic variable of exposure.
Socioeconomic variables such as education, income, gender4 4.
Of all the domains analyzed,at least one socioeconomic variable was associated with lower scores of quality of life.
Socioeconomic variables were family income, education and profession.
Most studies of these helminth are concentrated in the socioeconomic variable leaving a gap for the environmental variables. .
The socioeconomic variables are important physical health correlates.
In the hierarchic analysis model used in the present study,the effect of a distal socioeconomic variable such as family income at birth would be related to the level of schooling of the youth.
The socioeconomic variables studied were level of education and income.
The association between schooling andoverweight among men vanished after adjustment for a hierarchically superior socioeconomic variable, such as family income, and for birthweight.
The socioeconomic variable proportion of heads of households with monthly income.
In this type of analysis, the variable that indicates the socioeconomic status of each neighborhood is named RIDIT, ranging from 0 to 1 andindicates the cumulative relative position of each observational unit in relation to a socioeconomic variable.
The only socioeconomic variable associated with overweight referred to years of schooling.
Because of the complementary nature of the different measures of socioeconomic status, we used the factor analysis method to evaluate this variable, with polychoric processing and orthogonal rotation,which allowed the construction of a single socioeconomic variable.
Socioeconomic variables were not associated with malnutrition or overweight.
In the present study, aiming to reduce the effects of residual confounding results,more than one socioeconomic variable were considered as possible factors of confusion: maternal age, family income and variables from the student birth weight, gender and age.
Socioeconomic variables were: marital status, education, occupation, income and housing.
Based on the results of the factor analysis,from which the extraction of only a single factor was satisfactory for the proposed multilevel analysis, the socioeconomic variable resulting from the sum of the three 2000 census variables Eigenvalue 2.44, proportion of variance explained of 97.7%, Cronbach's alpha of 0.74 was created and was subsequently divided into tertiles.
The socioeconomic variable that revealed the greatest difference between schools was the presence of a bathroom in the house.
As an outcome, were outlined specific objectives of the work: check if there willingness to pay on the part of the respondents with regard to urban areas of manaus; determine the value of willingness to pay for the environmental benefits of urban trees in manaus;relate cause effect of socioeconomic variable in relation to the value of willingness to pay estimated.
The socioeconomic variable that presented an association with PPD was family income, reitirating a similar result in other studies.
The effect of the individual variables on the association of the contextual socioeconomic variable was measured by the sequential addition of the groups of demographic and socioeconomic variables and by the calculation of changes in the odds ratio OR and their 95% confidence intervals CI.
The socioeconomic variable was calculated from a combination of the following socioeconomic indicators: income, number of family members, schooling, housing and family members' occupation.
Thus, through employing an analytical model that controlled the socioeconomic variable, the results showed no academic advantage of the children with two years of ECE in relation to their colleagues with one year of ECE; thus, the first question investigated in the study received a negative response, contrary to previous studies with positive results Curi& Menezes-Filho, 2006; Entwisle& Alexander, 1998.
The socioeconomic variable proportion of heads of households with monthly income< 1 minimum salary was the only variable to show a statistically significant association, thus indicating that the risk of death due to these causes was more associated with low income than with proximity to the landfill sites.
Dart analyzed the socioeconomic variable and its relationship with the use of the internet among 758 Australian individuals from three different communities low income, average income, and college students.
Regarding the socioeconomic variable, considering both groups, it was verified that category E inferior-high presented the highest frequencies, followed by category D middle-low.
The contextual socioeconomic variable was associated with the outcome of interest in all models evaluated. However, the magnitude of this association decreased when individual socioeconomic variables were included.