Sentences with phrase «for socioeconomic variables»

And the link remained significant even after the researchers controlled for socioeconomic variables, like parental education level and occupation.

Controlling for socioeconomic variables, there are no big differences between the private and public system in the SIMCE.

Several studies have also attempted to understand the role of breastfeeding on IQ, and although some authors conclude that the observed advantage of breastfeeding on IQ is related only to genetic and socioenvironmental factors, a recent meta - analysis showed that after adjustment for appropriate key co-factors, breastfeeding was associated with significantly higher scores for cognitive development than formula feeding.6 Longer duration of breastfeeding has also been positively associated with intelligence in adulthood.22 We also observed the benefits of long - term breastfeeding on mental indices, along with the indirect benefit of balancing the impact of exposure to p, p ′ DDE after adjustment for some socioeconomic variables.

Not exact matches

The research, compiled by the Harvard School of Public Health's Injury Control Research Center, is pretty clear: After controlling for variables such as socioeconomic factors and other crime, places with more guns have more gun deaths.

They controlled for other variables like socioeconomic status and the weight of the children who ate school lunches had significantly increased.

Being breastfed exclusively for at least four months has been shown to have a positive effect on the intellectual development of children even when controlled for the demographic variables, especially socioeconomic status (SES) and education of the mother.14 - 22 The nutrient advantages of human milk coupled with the mother - infant relationship provide the matrix for the child to reach his / her full intellectual potential.

In a study of relationships between socioeconomic variables and opioid - related drug overdoses, researchers found several correlations that are often not discussed in the current conversation about the nation's deaths of despair, which includes opioid overdoses, said Stephan Goetz, professor of agricultural and regional economics, Penn State and director of the Northeast Regional Center for Rural Development.

Socioeconomic variables were obtained from a database for health insurance and labour market studies.

«The discordant twin design minimizes a number of potentially confounding factors that may explain the association between childhood verbal ability and subsequent alcohol use by «controlling» for differences on variables [such as] socioeconomic differences or family factors that, if excluded, could cloud the interpretation of findings.»

The problem, however, when looking at simple correlations between social media use and STDs is that they fail to control for many other socioeconomic variables that can be related to sexual behavior and an increased risk of contracting an STD.

In order to isolate the effect of social networking on STD prevalence, the study controlled for a range of socioeconomic variables including population, race, age, income, education, and population density.

In this study, many of these socioeconomic variables were controlled for, including population, race, age, income, education, and population density.

[8] While individual - level models controlling only for race and gender showed blacks more likely to be identified, adding a family socioeconomic status variable eliminated the effect of race for blacks, while Hispanics and Asians were significantly less likely to be in special education.

Once we adjusted the data for the effects of socioeconomic status, birth weight, participation in WIC, and a few other variables, we were able to fully account for the difference in test scores.

Even controlling for such variables as socioeconomic status, 10th grade math scores, parents» birthplace, sex, and region, bilingual education has unambiguously negative effects on both years of education and attainment of a degree.

Mariam, Yohannes (1999): Causal Relationship Between Indicators of Human Health, the Environment and Socioeconomic Variables for the OECD Countries.

My understanding is that the socioeconomic variables are a proxy for human activity & infrastructure — waste heat & asphalt — which are more concentrated in urban areas, and are probably on the rise throughout most of the world through the post-war 1950s - 80s.

Separate χ2 analysis for gender, socioeconomic status, and race indicated no significant relationship between attrition and intervention condition for these variables.

Initially each variable of interest was included in a separate model controlling for age, sex, ACCHS, carer's employment status (as a measure of socioeconomic status) and clustering by family ID.

SLA - level predictor variables will include: accessibility (ARIA +), 33 socioeconomic status (using Socio Economic Status for Areas (SEIFA) indexes, four indexes that summarise different aspects of the socioeconomic conditions of people living in an area based upon sets of social and economic information from the Australian Census35); full - time equivalent GPs; medical workers, nurses, pharmacists, Aboriginal health workers and community services workers per 10 000 population; rates of unemployment and labour force participation.

In this study, data from a sample of 310 married couples was examined for relationships between indicators of marital satisfaction, socioeconomic variables, religiosity and finances to determine their impact on individual decisions to remain in relationships.

The results of Pearson correlation analysis and hierarchical regression analysis revealed a statistically significant rela - tionship between job and life satisfaction, even after controlling for demographic and socioeconomic variables.

Given that CfC and comparison sites are matched on the socioeconomic index for areas, which comprises over 30 area - level variables, it was not necessary to include area characteristics as control variables.

Multiple logistic regression analyses (Table 3) yielded the following results after controlling for age, sex, race and ethnicity, and socioeconomic background variables.

Having controlled for demographic and socioeconomic variables, the age variable was uniquely predicted job satisfaction.

It is likely, for instance, that these homes differ in socioeconomic status (whether or not this variable was recorded), which means that the unfavorable home is apt to be more crowded and located in a different sort of neighborhood.

Evidence for the test's concurrent validity with the variables age, gender, and socioeconomic status was also obtained.

Area - level explanatory variables will include: accessibility and remoteness, as measured by the Accessibility / Remoteness Index of Australia Plus (ARIA +); 54 socioeconomic disadvantage, as measured by the Australian Bureau of Statistics (ABS) Socioeconomic Indexes for Areas (SEIFA); 55 presence of Aboriginal Medical Services; presence of an AMIHS; proportion of Aboriginal pregnancies / births in an area managed by an AMIHS; numbers of Aboriginal and non-Aboriginal children attending preschool; numbers of full - time equivalent health workers (including general medical practitioners, nurses, midwives and Aboriginal health workers) per 10 000 population; measures of social capital from the NSW Population Health Survey; 56 features of local communities (derived from ABS Census data), such as information on median personal and household income, mortgage repayment and rent; average number of persons per bedroom and household size; employment; non-school qualifications and housing type for Aboriginal residents insocioeconomic disadvantage, as measured by the Australian Bureau of Statistics (ABS) Socioeconomic Indexes for Areas (SEIFA); 55 presence of Aboriginal Medical Services; presence of an AMIHS; proportion of Aboriginal pregnancies / births in an area managed by an AMIHS; numbers of Aboriginal and non-Aboriginal children attending preschool; numbers of full - time equivalent health workers (including general medical practitioners, nurses, midwives and Aboriginal health workers) per 10 000 population; measures of social capital from the NSW Population Health Survey; 56 features of local communities (derived from ABS Census data), such as information on median personal and household income, mortgage repayment and rent; average number of persons per bedroom and household size; employment; non-school qualifications and housing type for Aboriginal residents inSocioeconomic Indexes for Areas (SEIFA); 55 presence of Aboriginal Medical Services; presence of an AMIHS; proportion of Aboriginal pregnancies / births in an area managed by an AMIHS; numbers of Aboriginal and non-Aboriginal children attending preschool; numbers of full - time equivalent health workers (including general medical practitioners, nurses, midwives and Aboriginal health workers) per 10 000 population; measures of social capital from the NSW Population Health Survey; 56 features of local communities (derived from ABS Census data), such as information on median personal and household income, mortgage repayment and rent; average number of persons per bedroom and household size; employment; non-school qualifications and housing type for Aboriginal residents in each area.57

They criticise, correctly, the failure of many studies to take account of socioeconomic variables and their effects, but they take apparently no account of possible genetic variables and other explanations for findings.

Emerson et al. [38 • •], for example, conducted a secondary analysis of the Millennium Cohort Study in the UK and found that after matching on socioeconomic variables, probable psychiatric disorder was no more likely to be found among fathers of children with early cognitive delay, and the strength of this association for mothers was substantially diminished.

The most apparent is that single measures of absolute concentrations of salivary cortisol, for most health - related variables, seldom give significant findings; deviation measures, in terms of diurnal deviations and / or laboratory stress tests seem to be more strongly and consistently associated with a number of factors, such as Socioeconomic Status (SES), psychological characteristics, biological variables in terms of overweight and abdominal fat accumulation, and mental and somatic disease.

Socioeconomic variables were also taken into account (in preparation for publication).

[jounal] Olsson, M. B. / 2008 / Socioeconomic and psychological variables as risk and protective factors for parental well - being in families of children with intellectual disabilities / Journal of Intellectual Disability Research 52 (12): 1102 ~ 1113

Variables for child's functioning (cognitive level [BAS Standard Nonverbal Composite (SNC)-RSB-; daily living impairment [VABS DLS Standard Score (SS)-RSB-; emotional and behavioural difficulties [SDQ Total problems]-RRB- and socioeconomic factors (income and educational level) were dichotomised into clinically meaningful subgroups in order to better capture their significance, as well as to facilitate the interpretation of the parameters (Ragland 1992).

Homeowner, type of dwelling and neighbourhood were not used in the final analysis because maternal education is highly correlated with all of these variables and provides a good proxy measure for socioeconomic status which was measured early in the study and is relatively complete.