Association
between sociodemographic factors, high social deprivation, poverty and increased risk of externalizing and internalizing disorders is also observed and the strongest association is that between moderately deprived neighborhoods and ADHD [23].
Structural equation models and regression analyses accounting for age and sex contributions revealed that emotion dysregulation mediated associations
between sociodemographic risk and internalizing symptoms, externalizing problem behavior, and drug use severity, and moderated links between psychosocial risk and internalizing symptoms and externalizing problem behavior.
There was strong evidence of a relationship
between sociodemographic variables and missing data on depressive symptoms (S2 Table).
There was strong evidence of a relationship
between sociodemographic variables and trajectories of conduct problems (S1 Table).
Responders and non-responders did not differ with respect to the prevalence rates of psychopathology and associations
between sociodemographic variables and mental health outcomes [11].
Next, we investigated the relationship
between sociodemographic characteristics and maltreatment.
To assess potential confounding, we examined group differences
between sociodemographic variables and basic needs at baseline.
Finally, we examined the association
between sociodemographic variables (child age, sex, race / ethnicity, maternal obesity, maternal education, poverty) and prevalence of having a chronic condition during any part of the 6 - year study period in multivariate logistic regression models that included all participants.
Not exact matches
To identify the energy contributions of NOVA food groups in the Mexican diet and the associations
between individual
sociodemographic characteristics and the energy contribution of ultra-processed foods (UPF).
No differences in anthropometric,
sociodemographic, or perinatal variables were found
between the groups who had (n = 345) or who lacked (n = 20) data on breast feeding.
The study noted: «A variety of
sociodemographic shifts, manifest in census data, could be causing these changes; however, because social change in the U.S.
between 1997 and 2007 centered on the expansion of communication technologies, we hypothesize that the sudden value shift in this period is technology driven.»
In addition, the researchers observed that
sociodemographic factors played a role, with an association
between areas of greater social deprivation and higher rates of opioid prescriptions.
Separate logistic models were used to calculate P values for the interaction
between levels of each
sociodemographic variable and seriousness of psychological distress to assess whether these AORs differed across strata.
OBJECTIVE To examine the association
between quality of life and health self - perception of children with poor school performance, considering
sociodemographic factors.
Hierarchical generalised linear mixed models with a logit link were used to analyse the relationship
between poor attendance and maternal alcohol use, and
sociodemographic and school characteristics, with models nested at the child and family level.
There were no differences
between the intervention and control groups in
sociodemographic background.
Results presented in tables 3 and 4 show the association
between geographic and
sociodemographic characteristics and the probability of being developmentally vulnerable on each AEDI domain by sex.
There were no statistically significant
sociodemographic differences
between the 2 groups.
Similarly, the size of
between - group differences in depressive symptoms may vary
between studies that used groups matched on
sociodemographic variables and studies that did not control for these
between - group differences, because the lack of control for demographic variables may cause unsystematic bias rather than a general overestimation or underestimation of
between - group differences in depressive symptoms.
Weighted bivariate and multivariate logistic analyses were used to assess the relationship
between maternal depressive symptoms (trichotomized to depression at both time points, at 1 time point, and at neither time point) and parental prevention practices, while controlling for a wide variety of
sociodemographic variables.
Multiple logistic regression analyses were used to determine the association
between panic attacks during adolescence in 1983 and the risk of personality disorders during young adulthood in 1993, adjusting for differences in
sociodemographic characteristics, adolescent personality disorders, and co-morbid depressive and substance use disorders.
Associations
Between Children's Consumption of Food Groups and Presence of Television at Meals, Controlling for Covariates and
Sociodemographic Factors †
Consumption of ultra-processed foods and associated
sociodemographic factors in the USA
between 2007 and 2012: evidence from a nationally representative cross-sectional study
The study aim was to examine the association
between coping strategies and self - efficacy in DM2 management in a group of 126 Mexican adults over 54 years old (= 68.57, SD = 7.19), which answered an interview about
sociodemographics data, self - efficacy in diabetes and coping strategies.
A significant association was found
between insecure attachment style and frequent attendance, even after adjustment for
sociodemographic characteristics, presence of chronic physical illness and baseline physical function [odds ratio (OR) 1.96 (95 % CI 1.05 — 3.67)-RSB-.
Sociodemographic characteristics were included as controls in the models on the basis of numerous studies that document associations
between these markers and behavioral outcomes.15 Multiple indicators of positive (eg, closeness, safety) and negative (eg, aggression, negative influence) dimensions of family, school, and community contexts were included on the basis of previous research.1, 7,11 — 15
The association
between critical life events,
sociodemographic data and physical activity in the development of myocardial infarction in smokers and ex-smokers
Associations
between group status and parent - reported outcomes were assessed via regression analyses controlling for
sociodemographic and health status variables.
Statistical analyses revealed a single self - regulation factor for this high neonatal risk sample, and this self - regulation factor mediated associations
between early
sociodemographic risk and mothers» ratings of academic competence and externalizing problems.
Even less is known of the mechanisms engendering the differential vulnerability of individuals in unions with varying degrees of
sociodemographic similarities
between spouses.
We examined associations
between variables in our main community sample using either simple logistic regression or multiple logistic regression (adjusted for
sociodemographic and other variables) to generate odds ratios and Wald tests.
There were inconsistent differences in some
sociodemographic factors
between our sample and the NATSISS: our sample had higher proportions of unemployed people, but also higher proportions who had completed Year 12 and who lived in more advantaged areas.
Associations
between the outcome variables and
sociodemographic and smoking variables were assessed using logistic regression to generate odds ratios (ORs) and P values based on Wald tests.
Lifetime prevalences of antisocial syndromes were estimated and logistic regression analyses were used to examine associations
between antisocial syndromes and
sociodemographic characteristics and substance use disorders.
There are relatively few studies examining associations
between staff characteristics and EE and no consistent evidence of associations with burnout, experience, training, or
sociodemographic factors.
However, these findings are not robust, as other studies have found no associations
between EE status and experience or training, 12,21,27,28 or associations
between age and other
sociodemographic variables.12, 21,28
A series of bivariate chi - square and F tests were conducted to examine whether significant relationships existed
between CJS involvement during the first 12 months of the trial and baseline measures of
sociodemographic characteristics, psychiatric status, substance abuse, and other patient characteristics.