All factors significantly associated with overweight/obesity (p < 0.10) in the bi-variable analysis such as sex, age, residence, marital status, occupational activities and socio-economic status, were included in the logistic regression model.
In the framework of variable exponent analysis such a condition first appeared in the paper [1], where the author established the boundedness of the Hardy-Littlewood maximal operator in.
Multivariate analysis assessed the clinical role of TUBB3, miR-200c, HuR pattern of staining in a model including additional significant variables in univariate analysis such as (age, stage and histotype) using the Cox proportional hazards model and nonparametric testing with the Kruskal Wallis test.
It could be used for successfully summarizing the inter-correlations among many variables obtained from the analysis, such as the cephalometric analysis data.
We also drop observations with missing information in variables used in the analysis such as age, education, income, state of residence, state of birth, occupation, industry, and population size (see Tables 1, 2 and 3).
We used this group of patients as a comparison group because we routinely measured all variables required for the analysis such as lactate and phosphate in these patients.
The other study design variables included in this analysis, such as study duration, did not significantly influence the proportion of isolates that were clustered, contrary to previous findings.
In the multiple linear regression analysis such variables as age, smoking status, BMI SBP, log HOMA-IR, log CRP, log TG, and TC/HDL-C ratio (PRE) or HDL-C (POST) were assayed as independent variables, whereas log A-FABP was assessed as a dependent variable.
In the single variable analysis, consuming other dairy products such as uncooked soft cheese, uncooked hard cheese, and cream were also negatively associated with illness.
The reversed social gradient in breast cancer risk may be explained by other variables not available in this analysis, such as BMI and exogenous hormone use, which have partially explained the association between SEP and incidence in previous studies [ 9, 41].
