In bivariate analyses, nonprofessional maternal occupations appeared to be associated with higher STD reports for all groups except white females (Table 3). Black females with mothers employed in office work (OR, 2.9; 95% CI, 1.1–7.6) and service or manual labor (OR, 2.8; 95% CI, 1.2–5.8) were more likely to report STDs than black females with mothers in professional occupations. Black males experienced similar or greater magnitudes of effect as black females, but these associations were less precise and not statistically significant. For white females, maternal occupation was not associated with STD reports in contrast to the other race-gender groups. STD reports appeared to be higher for white males with mothers in nonprofessional occupations with strong associations for service and office-position categories, but these associations were imprecise.
After adjustment, associations between nonprofessional maternal occupations and reported STDs increased slightly for black females (Table 4). For the other race-gender groups, these associations changed little, typically toward the null.
In bivariate models, self-reported STDs were consistently higher for those living in single-father, nonparental, or foster homes (Table 3). For all groups, the odds of STDs were approximately 2 times higher for adolescents in these households compared with those in 2-parent homes. Single-mother households were not strongly associated with STDs for black females, black males, and white females. With only 1 STD report among white males in single-mother homes, a negative association with STDs was found. After adjustment, most household composition-STD associations remained unchanged or decreased slightly (Table 4). Household composition associations increased for black males to 2.9 times (95% CI, 1.1–7.5) higher odds of STDs for other household types and 2.0 times (95% CI, 0.7–5.8) higher odds of STDs for single-mother homes when compared with 2-parent homes.
A possible association of lower household income and STD reports was observed only among black males (Table 3). In the lowest-income group, STD odds for black males were 2.7 (0.5–15.4) times higher than those with the highest income, but this estimate is imprecise. The associations between lower household income and reported STDs changed little in multivariate analysis (Table 4).
As a result of the high level of missing household income data (26%), which was unlikely to be missing at random,12 we performed a sensitivity analysis of unadjusted income-STD associations with missing incomes replaced with different values. Associations for black females, white females, and white males varied little across the different replacement methods (Table 5), suggesting that income was missing approximately at random in these groups. For black males, however, when missing values were placed into the lowest-income group, the results were similar to complete case associations. Given that STDs were more prevalent among black males with missing income (9.2%; 95% CI, 3.9–14.4) than those with income data (6.0%; 95% CI, 3.4–8.5), these differences suggest that reported crude and adjusted lower income-STD associations for black males could be underestimates of the true association.
The relationships among SES, race, gender, and negative health outcomes have been repeatedly identified as important public health issues.12,22–24 However, these associations are difficult to assess because of complexities in the relationships among race, gender, and SES, as well as the difficulty in identifying appropriate SES measures.8,9,11 In this examination of family SES and adolescent self-reports of STDs, we performed analyses stratified by race and gender, because direct comparisons have limited validity owing to the inability to adjust for the myriad of factors responsible for observed differences. We examined 4 SES measures to assess differences in their associations with adolescent STD reports for these race-gender groups.
We observed substantial differences in the family SES and STD relationships by race, gender, and SES measure. Generally, measures indicating lower SES were more consistently related to STD among blacks. Family structure, maternal occupation, and, to a lesser extent, maternal education were associated with STDs among black females and males. For black males, the association of STDs with maternal education and occupation were not statistically significant; however, the magnitude of the point estimates were comparable to those of black females, suggesting important, but imprecise, effects. In contrast, only nontraditional family structure was associated with STD among white females. Income was generally a poor indicator of STD risk in all groups, as expected.
The observed differences in the association of SES measures and STDs by race and gender could represent racial differences in contextual and individual risks. The single absolute, and difficult-to-measure, risk factor for STD acquisition is sexual contact with an infected partner. One step removed from this risk factor is participation in a sexual network with infected persons. In the United States, sexual networks are highly segregated by race.25,26 Furthermore, the geographic distribution of blacks and whites by SES is not equivalent. Lower SES blacks tend to be concentrated in urban areas and the rural southeast,27 both areas with a high prevalence of STDs. In contrast, lower SES whites are spread throughout rural areas in the remainder of the United States, which tend to have low STD prevalence. Our results suggest that for blacks, economic advantage, measured by maternal education or maternal occupation, could be associated with removal from a high STD-prevalence sexual network to a lower-risk network, perhaps through relocation to a more affluent area. In contrast, white adolescents with lower SES could be living in areas with historically low STD prevalence. It would be of interest to assess the contextual settings that these adolescents reside within to determine whether the geographic context of their communities are clearly associated with the individual SES measures and STD prevalence.
We expected family SES to have a stronger impact on adolescent STDs because family SES should affect the adolescent's proximity to and interactions with high-risk sexual networks. We anticipated that family SES would influence residential location,26,28,29 access to health care, particularly STD screening,30–32 and parental capacity to discuss sexual risks.29,33–43 Instead, the relatively weak associations found suggest that family SES might be less important than other factors such as individual risk behaviors and community-level influences, including community SES. Individual factors such as number of sexual partners and trading sex for drugs or money have been associated with STD reports in racial-gender subgroups.44 Additionally, when adjusted for individual risk behaviors, black-white disparities in adolescent STDs were reduced, whereas they increased when adjusted for SES.7 Although neighborhood poverty levels were not found to consistently reduce racial disparities in adolescent STDs,40 other community-level influences such as income inequality, segregation, and social capital investment have yet to be investigated and could prove to be critical for disparities in adolescent STDs as they have for other types of health disparities.6,12,45–47
We did not anticipate an absence of association between maternal education or occupation and STDs for white females. In addition to the potential contextual explanations, differences in individual risk behavior could contribute to the observed differences in SES measures. Among female adolescents, lower parental education has been associated with early sexual activity but not with number of sexual partners,48 suggesting less variation in sexual risks across SES levels for white females compared with other groups. Although we adjusted for the number of sexual partners, we could not assess other partnership characteristics such as concurrency49,50 and partnership age or racial disparity,26,49,51–54 which could affect white female SES-STD associations.
Unfortunately, in the United States, race remains a marker of STD prevalence. The substantial disparity in STDs by race is unlikely to be the result of biologic mechanisms, but rather, results from a complex interaction of individual and contextual factors, including SES. The complexity of these numerous relationships contributes to the fact that observed racial disparities cannot be adequately assessed in single models directly comparing racial groups. In epidemiologic terms, direct race comparisons are difficult to justify because the implicit counterfactual comparison is not justifiable.8–10 By examining the relationship of SES measures and STD after stratification by race and gender, we clearly demonstrated that the association of these measures with STDs differs by race, which supports our underlying rationale for using this stratified approach.
SES is a multifaceted construct that cannot be described adequately with a single measure. We observed, as have others investigating similar outcomes including adult STDs55 and adolescent initiation of sexual intercourse,48 that household income had weaker associations than other SES measures. Although measurement error and missing data are plausible explanations for this weak association, income could simply not reflect the complexity of SES. Other measures of family SES such as wealth,12,56 parental (not only maternal) measures, or composites of multiple SES measures56 could have provided different insights than the 4 SES measures used.
Our selected socioeconomic indicators have potential limitations, including appropriateness, number of missing observations, differential reporting, and measurement error. We held the SES variable categories constant across race-gender groups to allow for comparison between the groups, but disproportionate representation in the categories could influence the observed results. With fewer blacks in the highest SES groups and fewer whites in the lower groups, we lose the ability to create categories representing the nonoverlapping tails of these distributions, which could be critical in health disparities.12,22,57 Also, the same absolute levels of SES do not imply the same level of benefits for each group with blacks and females benefiting less than whites and males at the same level.11,22
The cross-sectional study design limits assessment of the causal relationship between SES and STD reports. However, directions of potential causal relationships are not in doubt because the family SES indicators (maternal education, maternal occupation, household composition, and annual household income) are unlikely to result from an adolescent's STD status. Temporality could be a problem, particularly in relation to other variables included in this study. The outcome includes infections occurring throughout the sexual histories of these adolescents, so we cannot be certain that risk behaviors and attitudes preceded STD diagnosis.58
Although the STD prevalences in this study are similar to those from other adolescent STD research,7 our prevalence underestimates the true prevalence of infections because it is based on self-reports. Potential causes for underestimation include underreporting, asymptomatic infections, and lack of screening in high-risk populations. Underreporting of STD diagnoses can result from embarrassment or misunderstanding of a diagnosis.59,60 In Add Health, audio computer-assisted interviews (A-CASI) were conducted to limit bias and nonresponse for sensitive items such as STD histories.61–64 Asymptomatic or mildly symptomatic infections are common among females and would be missed unless screening occurred.65,66 Female patients commonly undergo STD screening, but regular contact with the medical system is less frequent for adolescent males. However, because sexually transmitted infections are more commonly symptomatic in males, treatment is typically sought.30,67
We combined multiple STDs in a single measure to maximize the STD prevalence. Different STDs could have distinct patterns of occurrence, which might be related to SES, possibly affecting observed results. Chlamydial infection was the most predominant STD in this sample; however, the use of a composite STD outcome measure limits the ability to interpret the results for any single STD.
Add Health used a school-based sample and did not include adolescents who dropped out of school before the survey. Consequently, youths presumably at high risk for STDs and relatively lower SES could have been excluded disproportionately.68 However, a recent evaluation of the adequacy of the sampling of Add Health suggests that bias arising from school dropouts could be minimal.69
STDs are among the most common health problems faced by American adolescents. Race,4,6,7,35,51,70–78 gender,4,51,74,79,80 and socioeconomic status6,7,81 have repeatedly been demonstrated to be associated with STDs among adolescents. However, more in-depth considerations of adolescent STD disparities have been limited. Our results demonstrate important differences in family SES and increased adolescent STD reports when stratified by race and gender. Future investigation of adolescent STD disparities, particularly with biologic measures of prevalent infections, should stratify by race and gender when possible. In addition, studies considering the role of SES should include multiple indicators. For most adolescents, family SES has minimal effects on STD risks, but other factors could still influence these outcomes, including adolescent-specific factors and community-specific factors.
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