Items on Race #17


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Health and Behavior Risks of Adolescents with Mixed-Race Identity
Abstract
Objectives. This study compared the health and risk status of adolescents who identify with 1 race with those identifying with more than 1 race.

Methods. Data are derived from self-reports of race, using the National Longitudinal Study of Adolescent Health (Add Health), which provides a large representative national sample of adolescents in grades 7 through 12. Respondents could report more than 1 race.

Results. Mixed-race adolescents showed higher risk when compared with single-race adolescents on general health questions, school experience, smoking and drinking, and other risk variables.

Conclusions. Adolescents who self-identify as more than 1 race are at higher health and behavior risks. The findings are compatible with interpreting the elevated risk of mixed race as associated with stress.

A considerable literature attests to the emotional, health, and behavior risk problems of mixed-race adolescents. The most common explanation for the high-risk status is the struggle with identity formation, leading to lack of self-esteem, social isolation, and problems of family dynamics in mixed-race households.1–6 This literature is not entirely consistent. In some studies no differences are found between mixed-race and single-race children.7–9 This article explores the risk status of self-identified mixed-race compared with single-race adolescents using a large, nationally representative sample.

Most studies are based on clinical reports or reports of mixed-race samples without comparison to single-race groups. It is not surprising that such samples lead to the conclusion of emotional and behavior problems, as clinical samples are self-selected for problems. No national data on adolescents have been reported, except from the sample we used.

In 2000, the Bureau of the Census introduced a new system of reporting race, providing a list of races and asking respondents to check all that apply. Because an adult in the household filled out the census, children and adolescents had their race reported by a household adult. The National Health Interview Survey (NHIS) has been using a check-all-that-apply race classification for data collection for 20 years, but data on the health of those reporting mixed race is only recently being reported.10 In the NHIS, race for adolescents and children is reported by a household adult.

These 2 national sources will provide new data on mixed-race adults and children. However, such data are not suitable for examining the racial identity of adolescents, as their race is reported by another person in the household.

We test the prevailing view of the literature that mixed-race adolescents are at higher health and behavior risk than single-race individuals because of stress associated with mixed racial identity. An alternative and simpler hypothesis is that mixed-race adolescents are affected by the cultural experience of both races and will have risk status in between their 2 component races. We test the hypothesis that mixed-race adolescents are within the boundary values for the nonrisk individual and family attributes of the 2 single-race groups that constitute their identities.

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METHODS
This study presents data comparing mixed-race adolescents with single-race adolescents in the National Longitudinal Study of Adolescent Health (Add Health), a nationally representative school-based probability sample of U.S. children in grades 7 through 12 in 1994–1995. A stratified probability sample of 80 high schools was selected from a list of all high schools. A feeder school was selected (by probability proportional to its contribution to the high school) for each high school where required, to provide a full range of grades. All students attending on a specific day in each school completed a self-administered op-scan questionnaire (a paper and pencil questionnaire with an electronic scoring sheet for answers to be recorded by the respondent) under the supervision of a classroom teacher. The questionnaire collected demographic characteristics, health and behavior reports, and race self-identification. Questionnaires were placed in a sealed envelope by the respondent when completed and deposited in a box for project staff pickup. Teachers had no access to the completed questionnaires.

About a year later, a probability subsample of school respondents (plus those on the school roster but not present at school administration) were interviewed at home, using a laptop questionnaire (questionnaire recorded in a laptop computer with answers electronically recorded) that was administered by an interviewer. Sensitive questions were self-administered using earphones to listen to the questions read from the computer while shown on the screen. The home interview collected a broader range of data than the school questionnaire. A parent or guardian was also interviewed for most respondents. The same race question was asked on the school, home, and parental surveys.

Add Health respondents were asked to identify their race answering the following question: “What is your race? You may give more than 1 answer: White, Black or African American, American Indian or Native American, Asian or Pacific Islander, Other.”

Racial reporting of respondents was based on self-identification in self-administered school questionnaires and interviewer-administered home interviews. Add Health used the check-all-that-apply technique, allowing respondents to choose as many races as they wished.

Cooney and Radina11 exploited another Add Health possibility for multiple race classification from this same data source. Cooney and Radina used the small, public use subset of Add Health cases and further limited their analysis to adolescents living with both biological parents, 1 of whom had provided a parental interview. Because only slightly more than half of Add Health respondents lived with both biological parents, this analytic strategy resulted in a much reduced sample size, consisting only of adolescents in biologically intact families. If the parent self-identified as 1 race and identified the other parent as another, Cooney and Radina classified the child as mixed race. This strategy does not provide the adolescents’ racial self-concepts. Parker and Lucas12 found that parents who reported a spouse of a different race did not necessarily report that their child was of more than 1 race.

This article uses the child’s report of his own race without reference to parents races. It should not be assumed that the child reported what parents or coresident adults would have reported for the child, nor that the parents would report themselves as the same race combination (if any) as the child self-reported. This self-identification assures us that the adolescent racial self-concept is what we are working with.

Measurement of Dependent Variables
Variables to be correlated with race were derived from both the self-administered school questionnaire and the home laptop interview. They fall into 3 general categories: risk variables (school questionnaire), risk variables (home interview), and nonrisk attributes (school and home surveys).

Risk variables (school questionnaire).
General health: Self-reported health—fair or poor (vs excellent or good); wake up feeling tired often or every day in last month; have skin problems such as itching or pimples often or every day last month; have headache often or every day in last month; have aches, pains, or soreness in your muscles or joints every day last month; have trouble falling asleep or staying asleep often or every day in last month; feel depressed or blue often or every day in last month.

Substance use: Smoked cigarettes at least 2 days/month during last 12 months; drink beer, wine, or liquor at least 2 days/month during last 12 months; get drunk at least 2 days/month during the last 12 months.

Risk variables (home interview).
Access to guns: Guns easily available in the home.

Suicidal thoughts: Seriously thought about committing suicide during the last 12 months.

Sexual behavior: Ever had sexual intercourse.

School behavior: Skipped school more than 10 times in the last year; repeated a grade; ever received an out-of-school suspension.

Nonrisk attributes (school and home surveys).
Vocabulary score/picture vocabulary test (PVT): Add Health short version of Peabody PVT,13 percentage in category that are above the overall 75th percentile (home interview).

Grade point average (GPA): Self-reported grades (averaged across school subjects), percentage in category with GPA above the 75th percentile for the sample as a whole (school questionnaire).

Family structure: Percentage in category who live with 2 parents (vs other; school questionnaire).

Family education: Percentage in category with at least 1 parent with a college degree (school questionnaire).

School questionnaires with sampling weights were completed by 83 135 respondents, and home interviews by 18 924 adolescents. Analysis is computed in Stata (Stata Corp, College Station, Tex) to adjust for differential probabilities of selection and clustering of the sample. Weighted analyses provide estimates that are representative of the adolescent U.S. population.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1448064/



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