SOCIOLOGY EDUCATION - American Sociological Association

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252 Crosnoe Table 2. Odds Ratios from the Logistic Regressions Predicting Wave III College Enrollment, by Gender (n = 4,865 girls and 4,055 boys) Variable Odds Ratios for Boys Odds Ratios for Girls Obesity .83 .50*** Selection Factors Grade level 1.07* 1.05 Non-Latino/Latina white a — — African American 1.30+ 1.26* Latino/Latina 1.09 1.02 Asian American 1.86*** 1.28 Other race/ethnicity 1.20 .54* Family structure (two parent) 1.97*** 1.82*** Parental education 1.46*** 1.60*** School level (middle) 1.15 1.03 School sector (private) .91 1.35 School minority representation 1.01+ 1.01*** School proportion of college-educated. parents 10.09*** 9.58*** Measured ability 1.02*** 1.02*** Athletic status 1.80*** 1.57*** Number of friends 1.02 .98 Involvement with friends 1.01 .97 Romantic involvement .84* .84* School Factors Proportion of obese girls .32 .17 Proportion of obese boys .07 .42 a White was the comparison category for the race/ethnicity dummy variables. *** p < .001, ** p < .01, * p < .05, + p < .10. 50 percent higher) of attending college when they attended schools in which obese girls were more numerous than when they attended schools in which they were the sole obese girl. Taking a different angle, obese and nonobese girls had roughly the same odds of attending college after high school if they attended schools in which obese girls were well represented, but nonobese girls had much better odds (about 50 percent higher) of doing so than did obese girls if they attended schools in which obese girls were rare. 3 As was already mentioned, different demographic groups have different standards for appearance, in general, and body size, in particular, and they also differ in expectations for and support of educational attainment. Thus, as an ancillary analysis, I estimated the same models for white, African American, Latino/Latina, and Asian American youths, respectively, and then for youths with college-educated and non-college-educated parents (results not shown). The results for boys were essentially the same, regardless of race/ethnicity or level of parental education. The results for girls demonstrated more variation. Although significance levels varied according to the sample size (e.g., ranging from 2,641 white girls to 319 Asian American girls), the basic results were surprisingly similar across the groups. Yet, the longitudinal association between obesity and college enrollment and the moderating effect of the proportion of obese girls in the school were slightly more pronounced among racial/ethnic minority girls (versus whites) and among girls with college-educated parents (versus those with parents who did not graduate from college).
Gender, Obesity, and Education 253 Obesity and Psychosocial Adjustment The previous analyses revealed that girls who were obese during adolescence were less likely to enroll in college in young adulthood, especially when they attended middle schools and high schools in which obesity was relatively uncommon. Because obese and nonobese boys did not differ in terms of college enrollment after high school no matter where they attended middle school or high school, the subsequent investigation of the psychosocial mechanisms linking obesity to college enrollment will focus only on girls. As was described in the Plan of Analyses, testing mediation first required that I establish that obesity predicts the psychosocial outcomes. Table 3 presents the odds ratios from logistic regressions predicting two internalizing symptoms—self-rejection and suicidal ideation—among girls only. As may be seen in the first column, obesity at Wave I was associated with greater odds of self-rejection at Wave II, net of the four sets of selection factors, as well as the Wave I version of self-rejection. 4 Specifically, the odds of self-rejection were 63 percent higher for obese girls than for nonobese girls. Because of the control for Wave I self-rejection, these odds capture increases in the odds of self-rejection between Wave I and Wave II that are associated with obesity. As may be seen in the second column, obesity was also associated with increased odds of suicidal ideation among girls. Additional modeling iterations included interaction terms between adolescent obesity and the two school-level obesity factors. No interaction term significantly predicted either of the two internalizing outcomes for girls. The first panel in Table 4 presents the exponentiated coefficients from Poisson models predicting two types of self-medication— alcohol and marijuana use—among girls. Obesity was associated with higher expected frequencies of both. After all selection factors, as well as the Wave I versions of both substance use variables, were controlled for, these two obesity coefficients just narrowly missed statistical significance at the .05 level. Again, adding interaction terms between obesity and the two school-level obesity factors revealed no significant across-school variations in the associations between Wave I obesity and either form of Wave II substance use for girls. Finally, the second panel in Table 4 presents the exponentiated coefficients from Poisson models predicting two types of academic disengagement—the number of class failures and truancy—among girls. Obesity at Wave I predicted class failures at Wave II, net of the selection factors and Wave I number of class failures. More specifically, obese girls had 24 percent higher expected frequencies of class failures between Wave I and Wave II than did their nonobese counterparts who had the same number of class failures at Wave I. Additional analyses revealed no significant interaction between girls’ obesity and either school-level obesity factor. Wave I obesity did not predict girls’ truancy rates at Wave II in the full sample. Yet, in the next modeling iteration (not shown), the obesity measure did interact significantly (p < .05), with the school-level factor indexing the proportion of obese girls in the student body. To interpret this interaction term, I again calculated the predicted frequencies of truancy for obese and nonobese girls in different types of schools. Nonobese girls did not differ in their rates of truancy across schools. On the other hand, obese girls had low truancy rates if they attended schools in which at least 10 percent of the student body was other obese girls, but they had the highest truancy rates of all girls when they attended schools with no other obese girls. In sum, girls who were obese at Wave I demonstrated significant or marginally significant increases in self-rejection, suicidal ideation, alcohol use, marijuana use, and class failure between Wave I and Wave II. At the same time, they demonstrated increases in truancy during this period if they attended schools with a low representation of obese girls in the student body. The results provide support—among girls at least—for Path A1 in Figure 1. Obesity, Psychosocial Adjustment, and College Enrollment Having confirmed Path A1, I now attempt to establish Path A2. Table 5 presents the partial results of a logistic regression model predict-
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