Electronic Journal of Human Sexuality, Volume 13, Oct. 26, 2010


Early Sexual Initiation among Urban African American
Male Middle School Youth in Baltimore City

Damiya E. Whitaker, Carolyn D. Furr-Holden,
Leah Floyd, Pritika Chatterjee & William W. Latimer

Department of Mental Health,
Johns Hopkins University Bloomberg School of Public Health,
Baltimore, MD


Correspondence should be directed to Damiya Whitaker, Johns Hopkins University Bloomberg School of Public Health, Department of Mental Health,
2213 McElderry Street, 4 th Floor, Baltimore, MD 21205 U.S.A. Tel: (410) 502-9500; Fax (410) 955-0237; E-mail: dwhitake@jhsph.edu.


Data regarding the etiology of problem-based child and adolescent outcomes indicates neighborhood socioeconomic status, land use mix, traffic danger, availability of drugs and alcohol and collective socialization are factors that influence or confound behavior among youth in urban areas. With socio-ecological models in mind, this study examined associations between early sexual initiation and neighborhood condition, externalizing behavior, drug use and perceived peer acceptance of drug use. One hundred and fifteen African American male adolescents (ages 11 to 15) enrolled in a randomized control trial provided the data for analysis. Logistic regression models showed older age, perceived peer acceptance of drug use and externalizing behavior were predictors of early sex initiation. Although physical and social hazards as well as resource depletion in urban centers creates increased risk for poor health and social outcomes among adolescents, no neighborhood effects were found in this study. Interventions to delay sexual initiation among urban African American male adolescents may benefit from focus on both socially, and ecologically, relevant influences.


For decades research findings have shown, across measures of well-being that youth reared in disadvantaged neighborhoods fare worse (Brooks-Gunn et al., 1997) from problem behavior and negative peer affiliations to emotional and school-based functioning (Jencks & Mayer, 1990). Accordingly, a key element of Bronfenbrenner's ecological view of human development holds that settings close to a child’s daily life affect emotional and behavioral learning and development. The wisdom from that work implies child and adolescent behavior is embedded in a social context where family, school, and community provide influences on social adjustment - both direct and indirect. In view of existing theoretical and empirical research concerning the neighborhood ecology and child and adolescent development, sexual risk taking among youth can also be critically examined within a socio-ecological framework.

Research by the Centers for Disease Control and others indicates when compared to female adolescents, male youth are more likely to report first intercourse before age 15, using substances before sexual activity and higher rates of unprotected intercourse (Centers for Disease Control, 2006; O'Donnell et al., 2001; Smith, 1997; Norris et al., 1996; Coker et al., 1994 ) . The work of Rosenthal & Smith et al (1999) identified socioeconomic status and family structure individual factors affecting early sexual initiation. Kinsman & Romer et al (1998) observed older age, male gender, poorer schools, and African American race as additional individual level factors that may affect early sexual initiation among adolescents. Their work also noted a belief, among sexually experienced adolescents, that their friends were sexually active as well. Santelli et al (2000) , after examining existing research on the relationship between race/ethnicity, family structure and income and adolescent sexual behavior, used a novel approach to the study of earlier sex initiation by examining urban neighborhood residence, single parent homes and peer norms, for example, as social contexts affecting early sexual debut.

Today, there is much empirical evidence showing urban poverty and the associated neighborhood features may induce stress response changes in youth attitudes and behavior (e.g. early sex and/or drug use initiation). For example, Pettit et al (1999), using a sample of youth whose parents regarded their neighborhoods as unsafe, examined peer contact and externalizing behaviors. In their work, unsupervised peer contact predicted a worsening of externalizing behaviors with perceived neighborhood dangerousness exerting a moderation effect (Pettit et al., 1999). In another study examining the effect of neighborhood characteristics on youth, Peeples & Loeber (1994) found positive associations between neighborhood socioeconomic disadvantage and severity and frequency of male delinquency. Perhaps informed by the preceding work, Connell et al (1995) examined the differential effects of neighborhood characteristics on youth by gender. Using a sample of predominantly poor African American adolescents, they found that census-based neighborhood risk was associated with lower academic achievement and school attendance among male youth. Lang and colleagues (2010), using a cross section of sexually active male and female adolescents from three urban areas, found that youth living in high risk environments were more likely to report having causal sex partners and to have a sexually transmitted infection. Taken together, these works suggest neighborhoods exert more influence on youth, male youth even more so, as they may be more likely to participate in activities in their communities and therefore benefit when resources are present and conversely suffer when they are absent (Ensminger et al., 1996).

According, in this investigation, we use a convergence of these socio-ecological theories and contexts, e.g. peers and urban neighborhood conditions (Santelli et al., 2000) , Jessor and Jessor’s developmental perspective noting that in early adolescence there is increasing opportunities for experiences outside the family which may shape social behavior (Stanton et al., 2001; Doljanac & Zimmerman, 1998; Black et al., 1997; Stanton et al., 1993 ; Jessor, 1991 ) and Aker’s social learning theory which proposes that one learns antisocial behavior through observational learning in his/her social environment (1973) as a framework for our examination of early sexual initiation, drug use and externalizing behaviors among urban African American males in early adolescence. We assert that residence in economically impoverished communities, particularly for urban African American male youth, may play a more significant role in early sexual activity due to exposure to what Albert Hunter (1985) called concentrated incivility: visual signs of antisocial behavior including verbal harassment on the street, open solicitation for prostitution and public intoxication as well as visual cues of deterioration including graffiti on buildings, broken windows, and garbage in the streets (Huizinga et al., 2007; Sampson et al., 2005; Perkins & Taylor 1996). Additionally, we hypothesize neighborhood risk will predict drug use, externalizing behaviors, family function, perceived peer acceptance of drug use and early sex initiation among urban male youth.


Participants & Procedure

Baseline data was collected from 119 African American male schoolchildren, aged 11 to 15, enrolled in the Neurological Influences on Drug Prevention Interventions; a randomized control trial examining the efficacy of Integrated Family and Cognitive-Behavioral Therapy (IFCBT) in promoting school achievement and preventing drug abuse among at-risk middle-school aged youth. In this setting, “at-risk youth” is defined as those exhibiting early warning signs of drug abuse such as delinquency, failing a grade and suspension. The schoolchildren were recruited and enrolled from community-based schools in Baltimore City and Baltimore County. The race/ethnic distribution of the Baltimore City School District is 89% African American and 8% white (National Center for Education Statistics, 2005) . The study staff conducted screening and enrollment calls from a master student list generated by the participating schools. Youth eligibility was determined by parent/guardian positive endorsement on inclusionary questions: 1) “has your child experienced problems including failing classes” or 2) “having a low grade point average in the past year,” 3) “ever repeated a grade”, 4) “ever been expelled” or 5) “suspended from school,” 6) “ever been discovered using alcohol” or 7) “ever been discovered using drugs,” or 8) “ever had any other significant problems.” Upon eligibility confirmation, parent/guardian consent forms were administered at the participating school, study site, or the home upon request. Thereafter, the eligible student was contacted at school and consented for participation. Students meeting DSM-IV criteria for substance use disorder, psychotic disturbance, acute suicidal ideation, or chronic medical problems were excluded from the study and referred to a community-based treatment provider.

Each participant was administered a comprehensive assessment which included the Family Assessment Measure III questionnaire, the Motivated Strategies for Learning Questionnaire, the Neighborhood Environment Scale and a structured clinical interview (e.g. extensive sociodemographic, neurodevelopmental and medical history information). Participants were then randomly assigned to one of four conditions: 1) Integrated Family and Cognitive Behavioral Therapy (IFCBT) 2) cognitive-behavioral component of IFCBT only, 3) family component of IFCBT only, or 4) psychoeducation (Latimer et al 2003). A urine sample was also collected at baseline and a multidrug screen panel was used to verify participant drug use self-report.

Participants and their parent/guardian received financial remuneration for the assessment and subsequent participation in the assigned drug prevention intervention. The Johns Hopkins Bloomberg School of Public Health Institutional Review Board approved the Neurological Influences on Drug Prevention Interventions in November of 2003; annual reviews and human subjects’ approvals have been maintained. Informed consent was obtained at baseline as well as permission for follow-up.


Internalizing and externalizing behaviors were obtained by ratings on the Child Behavior Checklist (Achenbach, 1991; Achenbach & Rescorla, 2001) . Both were used as independent variables in the regression models (Jessor, 1991) . The Child Behavior Checklist ( CBCL) is a 113-item instrument, used with youth aged 5-18. It elicits reports of problem behaviors on several dimensions: internalizing and externalizing behaviors. Instrument items are rated on a 3-point scale and tallied to yield a composite internalizing and externalizing problem behavior score. T-scores greater than 59 suggest borderline or clinical impairment in that domain; reliability and validity of the CBCL has been established (Achenbach, 1991; Achenbach & Rescorla, 2001) . Internalizing and externalizing behavior scores were computed for each adolescent and dichotomized using clinically significant syndrome cut-points as defined by the CBCL manual.

Perception of neighborhood environment was obtained via responses on the Neighborhood Environment Scale (Crum, Lillie-Blanton, & Anthony, 1996) . Items included query on observable crime, filth, public drug use/alcohol consumption and perceived safety (Crum, Lillie-Blanton, & Anthony, 1996) . Responses were scored as “yes/true” (=1) or “no/false” (=0). A higher score indicated more perception of neighborhood disadvantage (e.g. more indicators of alcohol or other drugs, increased evidence of criminal activity and excess noise/disorder in the community).

To assess perceived peer acceptance of drug use, adolescents were asked to indicate whether their friends’ perceived drug and alcohol use as “very bad,” “it’s sort of bad,” “it’s not so bad as long as you don’t get into trouble” or “it’s not so bad/its okay.” The resultant ranking was dichotomized: adolescents answering, “it’s not so bad/ it’s okay” were compared to the adolescents who answered, “very bad,” “it’s sort of bad” or “it’s not so bad as long as you don’t get into trouble.” In other studies, similar questions have been used to illicit perception of peer norms regarding sex or drug and alcohol involvement (Kinsman & Romer et al., 1998).

Family function ratings were obtained from the Family Assessment Measure III (FAM III), a 50-item general scale including query on task accomplishment, communication, role performance, values and norms, affective expression, social desirability, involvement and defensiveness (Skinner et al., 2000) . Responses were scored from “strongly agree” (=0) to “strongly disagree” (=3) with some reversed scored items. An overall rating of family functioning was then computed with lower scores representing lower overall family functioning (Skinner et al., 2000) . The FAM III for children has high internal validity and is supported by an alpha coefficient of .94 (Skinner et al., 2000) .

Indicators of sexual initiation was determined from participant responses to “have you ever had sexual intercourse;” responses were scored as “yes/true” (=1) or “no/false” (=2). For “yes/true” (=1) responses, participants were asked to provide the age of first sexual intercourse. Those indicating a “no/false” (=2) response were used as the referent group.

Independent Variables

Substance use, age, free lunch (as a surrogate for social economic status), drug use, internalizing and externalizing behaviors as well as perception of neighborhood environment, perceived peer acceptance of use and ratings of family functioning were used as an independent variables due known associations with problem behavior (Grant, 1998; Warner & White, 2003) . Social economic status was measured by eligibility for free lunch. Estimates from the National Center for Education Statistics indicate 71% of adolescents in the Baltimore City school district receive free lunch, this is compared to the Maryland state average of 32% (2005) .

For this study, we were interested in substances commonly used by adolescents, primarily alcohol and marijuana (Kogan, Berkel, Chen, Brody, & Murry, 2006) , and their association with early sexual initiation. Among middle school youth alcohol, tobacco or other drug use is commonly defined as “ever used in your lifetime;” in this study, a binary variable was created for “ever used alcohol or marijuana in your lifetime.”

Missing Data

Only the male schoolchildren who self-reported their race as African American (N=119) were chosen for inclusion in this analysis. Four participants were excluded from the analysis due to missing data on the sex initiation variables; this resulted in a final sample of 115 African American male adolescents. Of the 115 participants that provided sexual initiation outcomes, 5 participants (4%) had missing data on either alcohol or marijuana use. Multiple imputation was used to impute missing data (Graham, Hofer, & Piccinin, 1994) .

Statistical Analysis

Logistic regression analyses were conducted to establish the relationship between early sexual initiation and specified independent variables. Independent variables including age, drug use, externalizing behavior, neighborhood risk and family functioning were added to the model singly and then together with other independent variables. Both crude and adjusted odds ratios and their 95% confidence intervals (CI) were computed and interpreted. All analyses were performed using SAS software 9.1. Hypothesis tests were two-sided and tested at an alpha level of .05. Descriptive statistics were used to summarize the sample demographics with means and standard deviations used to describe distributions of continuous variables, and counts and percentages used to describe categorical variables. The multiple regression model fit was good using the Hosmer and Lemeshow Lack of Fit Test (Chi-Square (df) =11.39(8), p=0.18).


Seventy-seven percent of the sample received free lunch at school (n=89), and the average age of the youth was 13.04 years (SD: 0.97). Forty-eight percent (n=55) of the sample had clinically significant externalizing behaviors, and 17% (n=19) reported ever having used alcohol or marijuana. The overall prevalence of early sexual initiation was 32% (n=37). Of those who reported sexual intercourse, approximately 19% (n=7) reported initiating at or before 10 years of age; 14% (n=5) reported initiating at age 11; 38% (n=14) reported initiating at age 12; 19% (n=7) reported initiating at age 13; and 11% (n=4) reported initiating at age 14.

Table I presents the sociodemographic results for the youth at baseline. Also in Table I are the unadjusted odds ratios. Older males were more likely to have reported sexual intercourse when compared to younger males (OR=2.07, 95% CI=1.30, 3.32). Also, externalizing behavior (OR=2.36, 95% CI=1.06, 5.27), drug use (OR=6.62, 95% CI=2.27, 19.49) and perceived peer acceptance of drug use (OR=4.87, 95% CI=1.73, 13.74) was associated with early sexual initiation. No relationship between economic status, internalizing behavior, neighborhood risk or family functioning and early sexual initiation was noted.

In the adjusted model, there was a significant association between age and early sexual initiation. Specifically, for every 1 year increase in age, the odds of sexual initiation increased by a factor of 1.88 (95% CI=1.09, 3.22). Perceived peer acceptance of drug use (AOR=3.74 95% CI=1.07, 13.07) was also associated with early sexual initiation. In this model, externalizing behavior and illicit drug use we no longer statistically significant and the estimates of the odds ratio were not as profound. This may indicate that other covariates in the model confound the relationship between sexual initiation in early adolescence and problem behaviors.


This study investigated links between neighborhood risk, family function, age, drug use, perceived peer acceptance of drug use, externalizing behaviors and early sex initiation among urban African American males in early adolescence . In the current study, the overall prevalence of sexual initiation was approximately 32% which is consistent with existing estimates of early sexual initiation among urban middle school youth (O'Donnell et al., 2001) . Additionally, early sexual initiation was associated with older age and externalizing behaviors was associated with drug use. These and other investigated associations between early sexual initiation and individual factors (e.g. peer perceptions) are consistent with extant literature (Kinsman & Romer et al., 1998; Shrier et al., 1996; Jessor, 1991) . For example, Tubman et al (1996), using a non-treatment sample of youth recruited from three suburban New York schools, found that once initiated sexual activity tended to be consistent and repeated intercourse tended to be associated with multiple partners, higher prevalence and earlier onset of externalizing behaviors, and higher levels of concurrent substance use. Using a Massachusetts-based adolescent sample, Shrier et al (1996) found that older age among adolescents was predictive of more years of sexual intercourse (1996). Further, in a study by Kinsman & Romer et al (1998), sexually experienced youth were found to be more likely to believe their peers were sexually active.

There were no neighborhood or socioeconomic effects noted in this study which is inconsistent with existing research (Browning et al., 2004; Cubbin et al., 2005) . One plausible explanation for this unexpected finding is Baltimore city has a greater proportion of poor neighborhoods as well as a disproportionate number of physical and social hazards (e.g. a homicide rate that is nearly 7 times the national rate). With that in mind, in order to test the hypothesis that urban neighborhood disorder exposure or risk induces maladaptive responsivity in youth (e.g. early sexual debut), the use of an objective neighborhood measure should have been considered. According to research, optimal measure of direct exposure to neighborhood conditions should be inclusive of query of residents as well as objective indices. Furr-Holden and colleagues (2008) created an objective neighborhood measure called the Neighborhood Inventory for Environmental Typology to quantify the specific malleable features of neighborhood structures and the social environment at the block level. In view of that work, future study refinements should include both a self-report and an objective neighborhood measure. Another probable explanation for the non-significant finding is the sample’s homogeneity; seventy eight percent of the sample received free lunch. Future research may want to compare early sexual initiation modified by neighborhoods with heterogeneous socioeconomic status. It is also worth mentioning, in both the crude or adjusted analyses, familial functioning was not significantly associated with sexual initiation. Future studies may also examine family functioning as it relates to family structure; such may provide insight into how family relationship models impact early sexual initiation (Rosenthal et al., 1999) .

The results of this study should be interpreted in view of its limitations. First, the study had a cross-sectional study design, a small sample size, and very specific population; such does not allow for inferences concerning temporal relationships and generalizability is limited. Second, self-report measures were used for investigating links between early sexual initiation and the other independent variables. While self-report measures are considered an important source of information, cross-validation of information from the adolescents’ parents and/or peers may have strengthened the study. In spite of the aforementioned limitations, evidence from this study suggests early sexual initiation prevention intervention designs should include strategies to target perception of peer sex and drug involvement as well as efforts to promote positive reproductive health in adolescence (e.g. informed sexual-based decision making, consistent contraceptive use and abstaining from drug use before/during sexual activity). Additional efforts to avert this phenomenon may also benefit from the inclusion of socially and ecologically relevant, and perhaps gender specific, interventions as well.


This research was supported by awards from the National Institute on Drug Abuse (NIDA) Drug Dependence Epidemiology Training Program (DDET) T32 DA007292 and DA015075 (Principal Investigator, William W. Latimer, PhD, MPH); the National Institute on Alcoholism and Alcohol Abuse (NIAAA) R01AA015196 Principal Investigator, C. Debra Furr-Holden, PhD; the Department of Mental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD; and the Intramural Research Program, NIH, National Institute on Drug Abuse. The authors would like to acknowledge the Neurological Influences on Drug Prevention Interventions study participants, the study coordinator, the study staff, and Dr. Sarra L. Hedden for statistical consultation.


Achenbach, T. M. (1991). Manual for the Child Behavior Checklist/4-18 and 1991 profile. Burlington, VT: University of Vermont, Department of Psychiatry.

Achenbach, T. M., & Rescorla, L. A. (2001). Manual for the ASEBA school-age forms & profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, & Families.

Akers, R. (1973). Deviant behavior: A social learning approach. CA: Wadsworth Publishing Company, Inc.

Black, M. M., Ricardo, I. B., & Stanton, B. (1997). Social and psychological factors associated with aids risk behaviors among low-income, urban, African American adolescents. Journal of Research on Adolescence, 7(2), 173-195.

Brooks-Gunn, J., Duncan, G., Leventhal, T. & Aber, J. (1997). Lessons learned and future directions for research on the neighborhoods in which children live. In J. Brooks-Gunn, G. Duncan, & J. Aber (Eds.). Neighborhood poverty: Context and consequences for children (Vol. 1, pp. 279-297). New York: Russell Sage Foundation.

Browning, C. R., Leventhal, T., & Brooks-Gunn, J. (2004). Neighborhood context and racial differences in early adolescent sexual activity. Demography, 41(4), 697-720.

Centers for Disease Control. (2006). Youth risk behavior surveillance-United States, 2005. Surveillance Summaries, Morbidity & Mortality Weekly Report; 55 (No. SS-5): 1-108.

Coker, A. L., Richter, D. L., Valois, R. F., McKeown, R. E., Garrison, C. Z., & Vincent, M. L. (1994). Correlates and consequences of early initiation of sexual intercourse. Journal of School Health, 64(9), 372-377.

Connell, J., Halpern-Felsher, B., Clifford, E., Crichlow, W. & Usinger, P. (1995). Hanging in there: Behavioral, psychological, and contextual factors affecting whether African American adolescents stay in high school. Journal of Adolescent Research, 10, 41–63.

Crum, R. M., Lillie-Blanton, M., & Anthony, J. C. (1996). Neighborhood environment and opportunity to use cocaine and other drugs in late childhood and early adolescence. Drug and Alcohol Dependence, 43(3), 155-161.

Cubbin, C., Santelli, J., Brindis, C. D., & Braveman, P. (2005). Neighborhood context and sexual behaviors among adolescents: Findings from the national longitudinal study of adolescent health. Perspectives on Sexual & Reproductive Health, 37(3), 125-134.

Doljanac, R. F., & Zimmerman, M. A. (1998). Psychosocial factors and high-risk sexual behavior: Race differences among urban adolescents. Journal of Behavioral Medicine, 21(5), 451-467.

Ensminger, M., Lamkin, R., & Jacobson, N. (1996). School leaving: A longitudinal perspective including neighborhood effects. Child Development, 67, 2400–2416.

Furr-Holden, C.D., Smart, M., Pokorni, J., Ialongo, N., Holder, H. & Anthony, J. (2008). The NIfETy method for environmental assessment of neighborhood-level indicators of violence, alcohol, tobacco, and other drug exposure. Prevention Science, 9(4), 245-55.

Graham, J. W., Hofer, S. M., & Piccinin, A. M. (1994). Analysis with missing data in drug prevention research. NIDA Research Monograph, 142, 13-63. Grant, B. F. (1998). Age at smoking onset and its association with alcohol consumption and DSM-IV alcohol abuse and dependence: Results from the national longitudinal alcohol epidemiologic survey. Journal of Substance Abuse, 10(1), 59-73.

Huizinga, D., Thornberry, T., Knight, K. & Lovegroove, P. (2007). Disproportionate minority contact in the juvenile justice system: A study of differential minority arrest/referral to court in three cities. Washington, D.C.: U.S. Department of Justice.

Hunter, A. (1985). Private, parochial and public social orders: The problem of crime and incivility in urban communities. In G. Suttles & M. Zald (Eds). The challenge of social control: citizenship and institution building in modern society. Norwood, NJ: Ablex.

Jessor, R. (1991). Risk behavior in adolescence: A psychosocial framework for understanding and action. Journal of Adolescent Health, 12(8), 597-605.

Kinsman, S. B., Romer, D., Furstenberg, F. F., & Schwarz, D. F. (1998). Early sexual initiation: The role of peer norms. Pediatrics, 102(5), 1185-1192.

Kogan, S. M., Berkel, C., Chen, Y. F., Brody, G. H., & Murry, V. M. (2006). Metro status and African-American adolescents' risk for substance use. Journal of Adolescent Health, 38(4), 454-457.

Lang, D., Salazar, L., Crosby, R. DiClemente, R., Brown, L. & Donenberg, G. (2010). Neighborhood environment, sexual risk behaviors and acquisition of sexually transmitted infections among adolescent diagnosed with psychological disorders. American Journal of Community Psychology [Epub ahead of print].

Latimer, W., Winters, K., D’Zurilla, T., & Nichols, M. (2003). Integrated family and cognitive behavioral therapy for adolescent substance abusers: A stage 1 efficacy study. Drug and Alcohol Dependence, 71, 303-317.

National Center for Education Statistics. (2005). Percentage of students eligible for free or reduced-price lunch and percentage enrollment that is other than white, non-Hispanic in the 100 and 500 largest school districts in the united states and jurisdictions: School year 2004-2005. Characteristics of the 100 Largest Public Elementary and Secondary School Districts in the United States: 2004-05.

O'Donnell, B. L., O'Donnell, C. R., & Stueve, A. (2001). Early sexual initiation and subsequent sex-related risks among urban minority youth: The reach for health study. Family Planning Perspectives, 33(6), 268-275.

Peeples, F. & Loeber, R. (1994). Do individual factors and neighborhood context explain ethnic differences in juvenile delinquency? Journal of Quantitative Criminology, 10(2), 141–157.

Perkins, D. & Taylor, R. (1996). Ecological assessments of community disorder: Their relationship to fear and crime and theoretical implications. American Journal of Community Psychology, 24, 63-107.

Pettit, G., Bates, J., Dodge, K., & Meece, D. (1999). The impact of after-school peer contact on early adolescent externalizing problems is moderated by parental monitoring, perceived neighborhood safety, and prior adjustment. Child Development, 70, 768–778.

Rosenthal, D. A., Smith, A. M., & de Visser, R. (1999). Personal and social factors influencing age at first sexual intercourse. Archives of Sexual Behavior, 28(4), 319-333.

Sampson, R., Morenoff, J., & Raudenbusch, S. (2005). Social anatomy of racial and ethnic disparities in violence. American Journal of Public Health, 95(2), 224–232.

Santelli, J. S., Lowry, R., Brener, N. D., & Robin, L. (2000). The association of sexual behaviors with socioeconomic status, family structure, and race/ethnicity among us adolescents. American Journal of Public Health, 90, 1582-1588.

Shrier, L. A., Emans, S. J., Woods, E. R., & DuRant, R. H. (1996). The association of sexual risk behaviors and problem drug behaviors in high school students. Journal of Adolescent Health, 20(5), 377-383.

Skinner, H. A., Steinhauer, P. D., & Sitarenios, G. (2000). Family assessment measures (FAM) and process model of family functioning. Journal of Family Therapy, 22, 190-210.

Stanton, B., Romer, D., Ricardo, I., Black, M., Feigelman, S., & Galbraith, J. (1993). Early initiation of sex and its lack of association with risk behaviors among adolescent African-Americans. Pediatrics, 92(1), 13-19.

Tubman, J., Windle, M., & Windle, R. (1996). Cumulative sexual intercourse patterns among middle adolescents: problem behaviors precursors and concurrent health risk behaviors. Journal of Adolescent Health, 18(3), 182-191.

Warner, L. A., & White, H. R. (2003). Longitudinal effects of age at onset and first drinking situations on problem drinking. Substance Use & Misuse, 38(14), 1983-2016.


Table I. Characteristics, Crude Odds Ratios and Adjusted Odds Ratio and 95% Confidence Intervals (CI)


N (%) or Mean (SD)

N (%) of Early Sexual Initiation

Crude Odds Ratio (95% CI)

Adjusted Odds Ratio†(95% CI)


13.04 (0.97)


2.07 (1.30, 3.32)**

1.88 (1.09, 3.22)*

Free Lunch (SES surrogate)






26 (22.61)

9 (34.62)




89 (77.39)

28 (31.46)

0.87 (0.34, 2.18)

0.39 (0.12, 1.30)

Externalizing Behavior





Not Clinically Significant

60 (52.17)

14 (23.33)



Clinically Significant

55 (47.83)

23 (41.82)

2.36 (1.06, 5.27)*

1.90 (0.63, 5.70)

Internalizing Behavior





Not Clinically Significant

68 (59.13)

20 (29.41)



Clinically Significant

47 (40.87)

17 (36.17)

1.36 (0.62, 3.00)

1.38 (0.52, 3.71)

Neighborhood Environment Scale

7.73 (3.06)


1.08 (0.95, 1.23)

1.03 (0.87, 1.21)

FAM III Total Score

58.62 (2.19)


1.21 (0.99, 1.48)

1.20(0.96, 1.48)

Illicit Use†






91 (82.73)

22 (24.18)




19 (17.27)

13 (68.42)

6.62 (2.27, 19.49)**

2.72 (0.70, 10.49)

Perceived Peer Acceptance of Drug Use





Wrong to Use

96 (83.48)

25 (26.04)



Not Wrong to Use

19 (16.52)

12 (63.16)

4.87 (1.73, 13.74)**

3.74 (1.07, 13.07)*

†Multiple Imputation procedures were used to calculate OR with missing data

*p<.05, **p<.01

Return to Front Page