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To explore the covariation of risk behaviors in a national sample of American Indian reservation-based youth using listwise principal components factor analysis and to determine how these risk behaviors may vary by age and sex.
Analysis of data from the National Indian Adolescent Health Survey, a validated anonymous self-report questionnaire of 162 items addressing various health domains.
The survey was administered nationally in more than 200 reservation-based schools.
Thirteen thousand nine hundred twenty-three reservation-based American Indian or Alaska Native students in grades 7 through 12 representing more than 50 tribes. The listwise factor analysis sample included 7687 respondents with complete data.
Main Outcomes Measures
Item loadings and factor correlations by age and sex for 30 risk behaviors across various health domains.
Three risk behavior factors were fairly stable across sex and age: (1) the use of alcohol, tobacco, and other drugs; (2) risky sexual behavior; and (3) suicidal behaviors. Correlations between these and other factors suggested different strengths of relationships by sex and age. Other factors, including violence, truancy, and delinquency, showed differences in item loading on factors and correlations between factors. The use of tobacco, alcohol, and other drugs was most frequently associated with other risk behavior factors, and suicidal behaviors showed the next highest frequency of intercorrelations.
There are sex and age differences in the covariation of risk behaviors, and suicidal behaviors should be further investigated to determine if our findings are unique to American Indian youth. Health interventions that focus categorically on 1 risk dimension should also emphasize substance use prevention and intervention. To prevent substance abuse among American Indian youth, research efforts need to focus on effective strategies for coping with social and psychological stressors.
DURING THE past decade, research has documented that many health-compromising behaviors of adolescents are strongly related to one another—a phenomenon known as covariation.1-4 Consistent findings include covariation between the use of tobacco, alcohol, and marijuana and the use of other drugs,1 sexual intercourse,5 and juvenile delinquency.4 Despite these findings, research limitations include a lack of understanding regarding whether age, sex, or ethnicity affect the type or strength of covariation among risk behaviors. Osgood6 argues that sex differences in covariation are the most widely reported, with tobacco use more strongly related to alcohol use, marijuana use, and delinquency for adolescent girls than for adolescent boys. Few of the studies he reviewed contained analyses for youth younger than 15 years. Such information is crucial if health promotion and disease prevention efforts are to be targeted more effectively to prevent the onset of health-damaging behavior and to intervene with health-jeopardizing behaviors that may not yet have crystallized into established lifestyle patterns.7
Investigators have also noted that data sets used for researching the co-occurrence of risk behaviors have included only a few dependent variables, precluding an examination of the full breadth of adolescent behaviors that may jeopardize health.4,8-10 In short, they do not permit a full explanation of the structure of health-compromising behaviors, the variation of this structure by sex, age, and ethnicity, and other critical variables.
Much research in this area has been limited to the white, middle-class, teenaged population,11 and little is known about adolescents growing up in poverty.12 For American Indian youth, this gap in understanding is particularly critical, as by any measure the health status of American Indian teenagers in the United States is below that of the general adolescent population.13 Stresses created by poverty and social disenfranchisement are evident.14,15 More than twice as many American Indians or Alaska Natives fall below the poverty line compared with all other races.16 Age-specific death rates among this population of adolescents reveal a picture of economic, psychological, and social stresses. The outcomes of risk behaviors are particularly severe. The death rate for American Indian or Alaska Native adolescents is twice that of adolescents of other racial or ethnic backgrounds; for American Indian adolescent boys, the rate is almost 3 times higher. In 1986, the rate of suicide for 15- to 19-year-old American Indians was 26.3 per 100000 compared with 10.0 per 100000 across all races for this age group.17 Deaths from unintentional injuries, particularly motor vehicle crashes, are also higher among American Indian youth than among any other ethnic or age group in the United States. Mortality in American Indian youth due to alcohol or other substance use is almost twice that of other races.18
This study used data from a national sample of American Indian youth to investigate the dimensions of risk behaviors that are strongly related to one another and to determine how these risk behaviors may vary by age or sex.
Participants and methods
Data for this study were obtained from the National Indian Adolescent Health Survey, a validated anonymous self-report questionnaire of 162 items addressing various domains, including physical and mental health, a range of health and risk behaviors, personal worries, school attitudes and performance, family and peer relationships, and other protective factors. Completed in 1990, the study was undertaken to provide a national portrait of the self-reported health and related behaviors of rural, reservation-based American Indian adolescents and to provide feedback to local tribes and communities so that the resulting prevalence data could be used for community mobilization and program and policy development.19 The survey was administered nationally to 13923 reservation-based American Indian or Alaska Native students representing more than 50 tribes; these students were in grades 7 through 12 in more than 200 schools. A final sample of 13454 youth were included in the working data set; extensive demographic information and specifications for data cleaning are detailed elsewhere.13 All study methods were approved by the Institutional Review Board of the University of Minnesota, Minneapolis. Although we recognized that differences exist between tribes, no tribal-level analyses were conducted to respect tribal confidentiality.
Thirty risk behavior items representing major threats to adolescent health and well-being were included in this analysis: alcohol, tobacco, and other drug use (marijuana, inhalants, other illicit drugs, cough syrup, and mouthwash); sexual behavior and pregnancy risk; suicide attempts; stealing and vandalism; fighting; gang involvement; skipping class and skipping school; and motor vehicle–related risk behaviors (riding with a drunk driver or driving drunk, lack of seat belt use, riding in the back of a pickup truck, and riding a motorcycle or 3 wheeler without a helmet). Reported behaviors, as opposed to attitudes, were examined to explain the structure of health-compromising behaviors in this population rather than to delineate attitudes, values, or expectations.20
An exploratory approach using listwise principal components initial factor extraction with oblique rotation was used to examine the co-occurrence of risk behaviors. With the use of factor analysis, the common elements or underlying variables (factors) among a large set of variables can be identified. Listwise analysis includes only those individuals who have answered all the items used to develop the factors. Oblique rather than orthogonal rotation allows for some level of correlation among health behavior factors.21
Previous research has demonstrated differences in risk behavior by age and sex.1,2,4,6 Thus, 3 sets of analyses were conducted. The first analysis focused on the total sample, the second investigated risk behavior differences by sex, and the third examined sex and age (older vs younger) differences. The criterion for item inclusion in any factor was an item loading of 0.30 or greater on a factor (ie, the correlation of an item with a factor). Then, correlations between factors were used to examine variations in the relationships between the risk behavior dimensions.
All items were coded such that higher scores represented riskier behaviors. Because of missing responses for the 30 items in this analysis, the listwise analysis total sample included 7687 respondents. Because some of the respondents were missing information about their sex or age, the sample sizes for age-by-sex comparisons were reduced to 2292 younger adolescent girls (aged 12-15 years), 1790 older adolescent girls (aged 16-18 years), 1936 younger adolescent boys, and 1615 older adolescent boys. Analyses were conducted to investigate potential sample bias due to missing responses. No significant (P>.05) differences were found in total number of items missing based on sex, age, self-reported grade in school, self-perception of academic ability, or alcohol, other drug, or tobacco use. In addition, a replication of the listwise analysis, using a pairwise data set, showed no bias in the listwise sample (ie, comparable loadings and correlations to the listwise analyses were found).
The oblique factor analysis of health-compromising behaviors in the total sample yielded 7 factors, depicted in Table 1. (The item descriptions are detailed in Table 2.) The factors in Table 1 explained 56.5% of the variance. Items relating to tobacco, alcohol, marijuana, and other drug use (excluding inhalants and the use of cough syrup or mouthwash to get high) and driving drunk or riding with a drunk driver loaded on factor 1. Factor 2 was composed of items related to risky sexual behaviors, while factor 3 included items pertaining to the history of suicidal behavior. These 3 factors explained about 39% of the variance.
Factor 4 for the total sample included items of gang involvement, vandalism, riding in the back of pickup trucks, and fighting. Items related to cheating at school, truancy, and delinquency loaded on factor 5. Truancy also loaded negatively with seat belt and helmet use on factor 6. Factor 7 included the use of inhalants and cough syrup or mouthwash to get high. Of the 30 behaviors analyzed, only 1, running away from home, failed to load on any factor at 0.30 or higher in the total sample analysis. Overall, the 29 behaviors yielded a structure of risk behaviors consisting of 3 dominant factors and 4 minor factors.
Correlations between factors of r=0.20 or higher are also provided in Table 1. Substance use (factor 1) was positively correlated with 4 other risk behavior factors. It was most highly correlated with sexual risk behavior (factor 2) and with delinquency or truancy (factor 5). It also was correlated with suicidal behavior (factor 3) and with violence or gang involvement (factor 4). Correlations of r=0.20 or higher were also found between suicidal behavior (factor 3) and violence or gang involvement (factor 4) and between violence or gang involvement (factor 4) and delinquency or truancy (factor 5).
Table 3 and Table 4 display the factor structure differences by sex. The first 3 factors continued to be almost identical to those in the full sample, except that the lack of seat belt use factored with the use of alcohol, tobacco, and other drugs for adolescent girls. Another noticeable difference was that truancy factored separately from delinquency for adolescent girls but not for adolescent boys. Vehicular behaviors of helmet use, seat belt use, and riding in the back of a pickup truck factored together for adolescent boys, while they were dispersed among 3 separate factors for adolescent girls. For adolescent boys and girls, the use of drugs other than alcohol, tobacco, and marijuana (including inhalants and cough syrup) factored with running away, although for adolescent girls this factor also included gang involvement and risky vehicular behaviors. Group fighting and beating up others factored with gang involvement for adolescent boys but with risky vehicular behavior for adolescent girls.
The use of tobacco, alcohol, and marijuana, driving drunk, and riding in a car with a drunk driver correlated most highly with risky sexual behaviors for adolescent boys and girls. For adolescent girls, these substance use–related items correlated almost as highly with suicidal behavior and with delinquency; for adolescent boys, they correlated next most highly with delinquency and with truancy. The only other factor correlation of at least r=0.20 for adolescent girls included risky sexual behavior and suicidal behavior. Among adolescent boys, 5 other factor correlations of at least r=0.20 included suicidal behavior with delinquency or truancy, with violence, and with the use of drugs other than tobacco, alcohol, and marijuana; delinquency or truancy with violence; and violence with the use of drugs other than tobacco, alcohol, and marijuana.
In sum, the analysis by sex revealed correlations of r=0.20 or higher for the use of tobacco, alcohol, and marijuana with risky sexual behaviors and with delinquency for adolescent girls and boys. However, differences in factor structure and intercorrelations were evident. Gang activity, vandalism, and interpersonal violence loaded onto 1 factor for adolescent boys but not for adolescent girls. Delinquency and truancy loaded separately for adolescent girls but not for adolescent boys. Finally, adolescent boys had many factor intercorrelations of at least r=0.20 or higher compared with adolescent girls.
Across sex and age groups, the derived risk factors explained between 57% and 60% of the variance. As shown in Table 5, Table 6, Table 7, and Table 8, factors 1 through 3 continued to remain consistent across age and sex groups. The only exceptions were that inhalant use factored with tobacco, alcohol, and marijuana use for younger teenagers but not for older teenagers and lack of seat belt use loaded with this factor only for younger adolescent girls. For younger adolescent girls, the use of inhalants, cough syrup or mouthwash, and drugs other than tobacco, alcohol, and marijuana also loaded with gang involvement and with running away from home, while for younger adolescent boys, these 3 items loaded with getting knocked out because of a violent injury.
The pattern of delinquency variables factoring separately from truancy still held for adolescent girls but also was evident for younger adolescent boys. For older adolescent girls, truancy was still composed of its own 2-item factor. For younger adolescent girls, truancy loaded with running away from home, which also held true for younger adolescent boys. For older adolescent boys, running away from home loaded with truancy or delinquency items and gang involvement. Gang activity loaded with items related to interpersonal violence across all age groups, although the constellation of other items that loaded with gangs varied by age and sex.
The disaggregation of sex and age also produced an eighth factor that explained less than 4% of the variance, differentially composed of items across groups, including the use of inhalants, cough syrup, or mouthwash as a drug, running away from home, and the nonuse of seat belts. Regardless of age and sex, the use of alcohol, tobacco, and marijuana consistently correlated with other dimensions of risk behaviors. It was a consistent correlate of sexual behavior and delinquency across age and sex groups, with the exception of younger adolescent boys. Among younger adolescent girls, it also correlated with suicidal behaviors; among older adolescent girls, it was linked with interpersonal violence and gang activity and truancy. Among younger adolescent boys, the use of alcohol, tobacco, and marijuana correlated with truancy and with the use of other drugs, while among older adolescent boys, it was associated with interpersonal violence and gang activity in addition to risky sexual behavior and delinquency.
Suicidal behaviors were also correlated with several other risk behaviors. In younger adolescent girls, suicidal behaviors correlated with the use of alcohol, tobacco, and marijuana and with delinquency; in older adolescent girls, suicidal behaviors correlated with risky sexual behaviors. In younger adolescent boys, suicidal behaviors were linked with the use of inhalants, mouthwash, and other drugs and with truancy or running away; in older adolescent boys, suicidal behaviors were linked with violence or gang activity.
In contrast, the relationship between sexual behavior and other dimensions of risk, besides the use of tobacco, alcohol, or marijuana, was weaker (ie, it was not a strong indicator of a generalized pattern of health risk behaviors). There was a correlation between risky sexual behaviors and suicidal behaviors among adolescent girls; however, it was above r=0.20 only for older adolescent girls.
This analysis highlights the consistency of 3 risk behavior factors across age and sex groups for reservation-based American Indian youth, including: (1) the use of tobacco, alcohol, and marijuana, drunk driving, and riding with a drunk driver; (2) risky sexual behaviors; and (3) suicidal behaviors. It also substantiates the relationship between alcohol, tobacco, and marijuana use and other risk behaviors, as evidenced by the number of stronger correlations between this factor and others across the 3 sets of analyses. These findings are consistent with those of other researchers who report positive correlations among the use of various types of drugs and the strong relationship between drug use and teenage sexual behavior.2,6
In contrast with the findings of Osgood6 that the level of covariation among risk behaviors does not seem to be substantially age or sex related, in this study various risk behavior items loaded differently by sex and age. As one example, the use of inhalants is more strongly associated with tobacco, alcohol, and other drug use for younger teenagers compared with their older counterparts. This provides evidence for the assertion by Beauvais et al22 that inhalants may be serving as "gateway" drugs among American Indian youth. Risky vehicular behaviors, with the exception of riding with a drunk driver or driving drunk, were also variable across sex and age groups. Furthermore, differences in patterns of covariation between the risk behavior factors were found among age and sex groupings. Most striking is the relationship between suicidal behaviors and other risk behaviors. Osgood6 cites the lack of large probability sample studies that allow for the analysis of suicidal behaviors with other risk behaviors. However, this data set, which included items related to suicidal behaviors, found correlations between this factor and other areas of risk taking. In fact, next to the use of tobacco, alcohol, and marijuana, the suicidal behaviors factor showed the greatest level of correlations with other risk behaviors.
This data set is unique in that it comprises the largest health behavior study of an indigenous youth population ever undertaken.19 Replication studies across large data sets, such as the new Add Health national data set on adolescent health and risk behaviors23 and the Indian-Focused Youth Risk Behavior Survey, will illuminate ethnic, racial, and sex variations in the interrelationships among factors.
Regarding health promotion and preventive strategies, the use of tobacco, alcohol, and other drugs among American Indian adolescents must be recognized as a warning for co-occurring risk behaviors. Our findings indicate that the heightened concern and attention in Indian communities toward substance use is warranted, not only because of the substance use itself but also because of the other potential accompanying risk behaviors. Health promotion programming for reservation-based American Indian young people should emphasize substance use prevention, even when such programs intend to focus categorically on other risk behaviors. Finally, the co-occurrence of suicidal behaviors with other risk behaviors must be addressed. The high rate of suicide among American Indian adolescents has been described as an especially troubling statistic among American Indian populations.24 Past research in American Indian communities has focused on psychopathological disorders, at the expense of understanding effective strategies for coping with social and psychological stressors.25
This analysis provides only 1 part of the equation in improving the health of American Indian adolescents. As discussed by Jessor,26 it is equally important to understand the protective factors that aid in promoting health. These factors are present in various domains, including the social environment, the youth's perceived environment, the youth's values, and the youth's protective behaviors. Preventing health-compromising behaviors and promoting health-enhancing behaviors are complementary objectives, and they require attention to physical, social, psychological, and personal health domains.27 In the American Indian community, such holistic approaches to health will need to be grounded in an understanding of the relationships between risk behaviors and the protective factors that promote health, using approaches that draw on the culture, strengths, and resilience of native communities.
Accepted for publication September 9, 1997.
This study was supported in part by grants MCJ279185 (Graduate Studies in Adolescent Nursing, School of Nursing, University of Minnesota, Minneapolis) and MCJ000985 (Adolescent Health Training Program, University of Minnesota Medical School–Minneapolis) from the Maternal and Child Health Bureau, Health Resources and Services Administration, Department of Health and Human Services, Washington, DC; the Office of the Vice President for Research and the Dean of the Graduate School of the University of Minnesota; and joint support for the original study from the Indian Health Service, Washington, and the Maternal and Child Health Bureau, Health Resources and Services Administration, Department of Health and Human Services.
Editor's Note: This study provides a comprehensive look at the dimensions of risk behaviors in American Indian youth. It should be valuable to all who care for and about them.—Catherine D. DeAngelis, MD
Corresponding author: Sandra J. Potthoff, PhD, Department of Healthcare Management, Carlson School of Management, University of Minnesota, 32119th Ave S, Room 3-140, Minneapolis, MN 55455 (e-mail: firstname.lastname@example.org).
Potthoff SJ, Bearinger LH, Skay CL, Cassuto N, Blum RW, Resnick MD. Dimensions of Risk Behaviors Among American Indian Youth. Arch Pediatr Adolesc Med. 1998;152(2):157–163. doi:10.1001/archpedi.152.2.157
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