Sentences with phrase «race or ethnicity factors»

«The coping experience, we imagine, is even more impacted by socioeconomic factors than race or ethnicity factors, but it continues to be challenging to recruit these diverse samples,» said Alessandri.

Not exact matches

And because of this, every person has innate value and is worthy of equal dignity and respect — regardless of race, gender, wealth, ethnicity, immigration status, background or any other factor.

Risk factors include: 1) age (most people are diagnosed in their 20s - 30s), 2) race or ethnicity (Caucasians have the highest risk, but IBD can occur in any race; there's an even higher risk if you are of Ashkenazi Jewish descent), 3) family history (risk is higher if a close relative has the disease), 4) cigarette smoking (the most important controllable risk factor for developing CD), 5) nonsteroidal anti-inflammatory medications (includes ibuprofen [Advil, Motrin IB, others], naproxen sodium [Aleve], diclofenac sodium [Voltaren], and others), and 6) where you live (you are more likely to develop IBD if you live in an industrialized country).

Is race or ethnicity a predictive factor in shaken baby syndrome?

Other factors that are also associated with increased prevalence rates include a history of incarceration or commercial sex work, geography, race / ethnicity, and being a male younger than 29 years.

Differences in race or ethnicity may lead to differences in factors that affect both fiber consumption and CRP concentrations.

And if it does manage a miracle and continue, Fuller said his choice to play rookie Clarice Starling would be Ellen Page or he'd switch up the ethnicity of the character and «have race play a factor in her character.»

In Hopwood, the appellate court held that schools could no longer use race or ethnicity as factors in admissions in Texas, Mississippi, and Louisiana.

New York City's progress in narrowing the achievement gap confirms that policymakers and advocates can no longer use demographic factors like race, ethnicity, income, or zip code to excuse differences in educational achievement between high - and low - needs students.

Fischer and Watson also expected to find that demographic and socio - economic factors such as race, ethnicity, gender, and socioeconomic status would lead to aggression, as earlier studies had indicated; instead, they found that these factors had little influence in whether or not a child became violent later in life.

Every student has the right to be educated, and that right can not be infringed by race, religion, ethnicity, sexual orientation, disability, economic status or any other factor granted to them by the U.S. Constitution.

Part of the reason for this shift is a recent U.S. Supreme Court opinion that suggested it may not be constitutionally sound for schools and districts to integrate solely based on students» race or ethnicity.15 Responding to this opinion, most school integration policies have shifted away from using race as a determining factor in student assignment.

Equity, when used in education, refers to all students receiving the same caliber of education regardless of the neighborhood they live in or their demographic characteristics, such as their race, ethnicity, special education status or other factors.

student performance in the context of gender, race / ethnicity, public or private school, teacher experience, and hundreds of other factors.

Our previous reports have explored topics such as what people do at libraries and library websites or how Americans value individual library services based on traditional factors such as gender, race / ethnicity, age, and household income.

Significant investments may be required to ensure that power generation keeps up with rising demand associated with rising temperatures.38, 39 Finally, vulnerability to heat waves is not evenly distributed throughout urban areas; outdoor versus indoor air temperatures, air quality, baseline health, and access to air conditioning are all dependent on socioeconomic factors.29 Socioeconomic factors that tend to increase vulnerability to such hazards include race and ethnicity (being a minority), age (the elderly and children), gender (female), socioeconomic status (low income, status, or poverty), and education (low educational attainment).

Workplace discrimination occurs when an individual is unfavorably discriminated against because of one or more factors, such as race, gender, religion, age, sexual orientation, or ethnicity.

This finding was present even while controlling for a number of potential confounding factors, including socioeconomic status and the child's age, race or ethnicity, and sex.

These included characteristics on multiple levels of the child's biopsychosocial context: (1) child factors: race / ethnicity (white, black, Hispanic, and Asian / Pacific Islander / Alaska Native), age, gender, 9 - month Bayley Mental and Motor scores, birth weight (normal, moderately low, or very low), parent - rated child health (fair / poor vs good / very good / excellent), and hours per week in child care; (2) parent factors: maternal age, paternal age, SES (an ECLS - B — derived variable that includes maternal and paternal education, employment status, and income), maternal marital status (married, never married, separated / divorced / widowed), maternal general health (fair / poor versus good / very good / excellent), maternal depression (assessed by the Center for Epidemiologic Studies Depression Scale at 9 months and the World Mental Health Composite International Diagnostic Interview at 2 years), prenatal use of tobacco and alcohol (any vs none), and violence against the mother; (3) household factors: single - parent household, number of siblings (0, 1, 2, or 3 +), language spoken at home (English vs non-English), neighborhood good for raising kids (excellent / very good, good, or fair / poor), household urbanicity (urban city, urban county, or rural), and modified Home Observation for Measurement of the Environment — Short Form (HOME - SF) score.

A covariate was included in the multivariate analyses if theoretical or empirical evidence supported its role as a risk factor for obesity, if it was a significant predictor of obesity in univariate regression models, or if including it in the full multivariate model led to a 5 % or greater change in the OR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor empirical evidence supported its role as a risk factor for obesity, if it was a significant predictor of obesity in univariate regression models, or if including it in the full multivariate model led to a 5 % or greater change in the OR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor if including it in the full multivariate model led to a 5 % or greater change in the OR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor greater change in the OR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dOR.48 Model 1 includes maternal IPV exposure, race / ethnicity (black, white, Hispanic, other / unknown), child sex (male, female), maternal age (20 - 25, 26 - 28, 29 - 33, 34 - 50 years), maternal education (less than high school, high school graduation, beyond high school), maternal nativity (US born, yes or no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor no), child age in months, relationship with father (yes or no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor no), maternal smoking during pregnancy (yes or no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor no), maternal depression (as measured by a CIDI - SF cutoff score ≥ 0.5), maternal BMI (normal / underweight, overweight, obese), low birth weight (< 2500 g, ≥ 2500 g), whether the child takes a bottle to bed at age 3 years (yes or no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / dor no), and average hours of child television viewing per day at age 3 years (< 2 h / d, ≥ 2 h / d).

Certain child and family characteristics may be associated with an increased risk of reentry into the child welfare system, including such factors as older age of the child (i.e., teens), children with behavioral issues or disabilities, and race / ethnicity.

Timelines for the matching and placement stages vary due to factors that the family is open to, such as: sex, race / ethnicity of the child, level of openness and ongoing contact with birth family, prenatal drug exposure and / or mental health diagnosis in the expectant parents, outreach options, the characteristics of the adoptive family, the fees the adoptive family is comfortable with, and the quality of the family profile.

Controlling for these two factors, in addition to controls for maternal age, age of youngest child, number of children, and race / ethnicity, eliminates or reverses differences in child care time between married and single mothers.

These findings suggest that race / ethnicity may be a risk factor for more negative or intrusive involvement by parents, whereas maternal education may serve as a protective factor for more positive collaborative involvement.