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The Black-White Disparity in Sexually Transmitted Diseases During Pregnancy: How Do Racial Segregation and Income Inequality Matter?

Noah, Aggie J. PhD*†; Yang, Tse-Chuan PhD‡§; Wang, Wei-lin PhD Candidate†¶

Author Information
Sexually Transmitted Diseases: May 2018 - Volume 45 - Issue 5 - p 301-306
doi: 10.1097/OLQ.0000000000000820

Eliminating racial health disparities in maternal and child health has been identified as one of the main goals of Healthy People 20201 as they can have serious lasting and cumulative implications for both women and their children. One important aspect of racial health disparities in maternal health2,3 is the acquisition of sexually transmitted diseases (hereafter, STDs) during pregnancy. Understanding the factors affecting the acquisition of STDs during pregnancy is particularly important for 3 reasons. First, rates of STDs during pregnancy are alarming. Second, in addition to the negative consequences associated with the acquisition of STDs for women’s reproductive health in general, the acquisition of STDs during pregnancy has heightened risks for both mothers and their infants,4 including serious pregnancy complications and perinatal mortality.5 Third, pregnant women can acquire an STD throughout her pregnancy. Although the risk of the acquisition of STDs decreases with increasing gestation as the frequency of sexual intercourse decreases, a nontrivial number of pregnant women (ie, 28% to 40%) are at continued risk of the acquisition of STD even during the later stages of their pregnancy.5 Together, these reasons demonstrate the need for more systematic research to promote screening and prevention of STDs for women throughout pregnancy.

Previous studies on the acquisition of STDs have used 2 approaches: an individual-centered approach that focuses on individual-level factors and an ecological approach looking at contextual-level STD rates.6 These studies have contributed to our understanding of various social determinants of STDs at multiple levels. Previous research using the first approach has found that various individual sociodemographic and behavioral factors contribute to the acquisition of STDs: race/ethnicity (particularly a membership in ethnic minority groups), lower education, poverty, a higher number of sexual partners, and delinquency behaviors.6,7 In addition, prior ecological studies have found that several contextual characteristics, such as racial/ethnic composition and social disorganization, are associated with STD rates at the aggregated level.6,8–10 Although these studies contribute to our understanding of social determinants of STDs, scholars and policy makers have started to move beyond these approaches by developing a multilevel research framework in which they simultaneously consider individuals and their neighborhoods.11–13 The multilevel approach can offer unique insights and notable contributions to the literature on social determinants of STDs as the acquisition of STDs is concurrently influenced by complex factors at multiple levels.14,15

Drawing from previous studies on neighborhood contexts and STDs,6,12 we specifically examine whether the black-white disparity in the acquisition of STDs during pregnancy could be explained by racial segregation and income inequality—2 critical contextual determinants of STDs in the multilevel framework.3 Building on previous ecological studies that found that contextual-level STD rates are associated with residential segregation2,16 and income inequality,16,17 this study investigates how residential racial segregation and income inequality are associated with the acquisition of STDs during pregnancy above and beyond mothers' individual characteristics. To the best of our knowledge, this study is the first to investigate how individual and neighborhood characteristics are concurrently associated with the acquisition of STDs during pregnancy using a multilevel approach. The current study contributes to the literature in 3 ways. First, we focus on STD acquisition during pregnancy as our main outcome, which has not been examined using the multilevel approach. Second, we apply the multilevel approach to the population data. Third, we use the residential segregation measures rather than simplistic racial/ethnic composition measures.


We obtained approval to conduct the research from the human subjects review board at the Pennsylvania State University. Data for this study come from 2 sources. The individual-level data are from the Commonwealth of Pennsylvania Department of Health Bureau of Health Statistics and Research—Master File Birth Extract. This data set is based on the total population of women who had a live birth in Pennsylvania during 2012 calendar year, and it includes detailed information on women’s prenatal health, birth experience, and birth outcomes. The contextual-level data are from 5-year estimates of the 2009 to 2013 American Community Survey. We use the census tract as a proxy for individuals' neighborhoods, which is a common practice in health research.18 Our analytic sample includes mothers who self-identified as non-Hispanic white (n = 79,271) or non-Hispanic black (n = 17,669). Defining neighborhoods with Census tracts, we had 96,940 respondents residing in 3138 neighborhoods for our analysis.

Individual-level Variables

The dependent variable used in this analysis, the acquisition of STDs during pregnancy, is measured as a dichotomous variable; women who acquired any of several STDs (ie, gonorrhea, chlamydia, syphilis, herpes simplex virus, or hepatitis B or C) during pregnancy are coded as 1. The presence of any of STDs is reported by doctors and/or hospital personnel who filled out the birth certificates.

Drawing from the literature, we include several individual-level sociodemographic factors. Maternal race is a dichotomous variable indicating whether a woman reported their race as non-Hispanic black (coded 1 if black). Maternal age at the time of infant’s birth is measured as the continuous variables age and age squared. If women were married at the time of infant’s birth, their marital status is coded as 1 and 0 if they were not married or in other marital statuses. A set of 3 dummy variables are created to measure maternal education: less than high school, high school diploma or equivalent degree, some college, and bachelor’s degree or higher. We use whether mothers received the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) as a proxy of maternal poverty status. We also include 2 pregnancy-related individual-level factors1: the total number of prenatal visits, a count variable indicating how many times women received prenatal care during their pregnancies, and2 a set of 3 dummy variables measuring women’s insurance status to indicate the method of payment for their delivery—namely, private insurance, medicated, self-pay, and other.

Neighborhood-level: Residential Segregation and Income Inequality

Although racial segregation can be measured with 5 dimensions,19 we focus on exposure and concentration because they are identified as the most relevant dimensions for infectious diseases.20 Exposure measures the degree of potential contact between groups within neighborhoods,19 and we assess this dimension with the isolation index measuring “the extent to which minority group members are exposed only to one another”.19 The dimension of concentration measures the relative amount of physical space a minority group occupies in the neighborhood. To measure concentration, we use the delta index, which indicates the proportion of a minority group that would have to move to produce a uniform density across neighborhoods. More detailed information on these measures is available elsewhere.19 In addition to the direct associations between residential segregation and STDs during pregnancy, we include the cross-level interaction terms (individual race × residential segregation indices) to test the potential moderating associations between residential segregation and STDs during pregnancy.

With respect to income inequality, we use 2 measures: a Gini index, which measures income inequality (relative measure of income distribution) and a poverty index, which assesses the absolute deprivation (absolute measure of income distribution). The Gini index is arguably the most common measure of income inequality; it ranges from 0, indicating no income inequality (ie, everyone has the same income), to 1, representing complete income inequality (ie, 1 person has all the income, whereas everyone else has zero income). Following previous research for creating neighborhood-level composite measures,21 we first use principal components analysis to confirm the emergence of 1 factor for 2 variables (see Appendix I, percentage of household living below the poverty line (factor loading = 0.92) and percentage unemployed (0.923). Then, we use the regression-weighted method to create the poverty index. Finally, we follow previous research22 in transforming the Gini index and poverty index into quintiles, because quintiles imply that the effects of Gini or poverty indices on STDs during pregnancy may be nonlinear. In our data, while data has missing values, to avoid potential selection bias, we adopt the missing data imputation approach to generate robust results. Specifically, we use multiple imputation methods (ie, mi command) to create 25 data sets in Stata to take the uncertainty of imputed values into account. We use a series of hierarchical logistic models.


Descriptive Statistics

Table 1 shows descriptive statistics for all variables included in the models for all women and by race. Overall, about 5.5% of women who had had a live birth in Pennsylvania during 2012 acquired STD during their pregnancies. This is similar to previous research, which estimated that about 1% to 5% of all pregnant women in the United States had chlamydia or gonorrhea.23 However, this percentage varies by race, with the number of mothers who acquired STDs during pregnancy about 3 times higher for blacks (12.1%) than for whites (4.1%). Other individual characteristics also vary by race. Whereas 67.6% of white mothers were married at the time of the birth, 20.6% of black mothers were married. Large differences appear in the educational attainment of white and black mothers. In addition, black mothers are more likely to be impoverished, with 68.3% of black mothers, but 28.3% of white mothers, receiving WIC benefits.

Descriptive Statistics of Variables at Both the Individual Level and the Contextual Level

The characteristics of the mothers’ neighborhoods vary considerably. On average, black mothers reside in highly segregated neighborhoods with an isolation index of 0.63, which indicates that black mothers have higher propensity to be exposed only to other blacks in their neighborhoods. In comparison, white mothers reside in less-segregated neighborhoods. Physical spaces occupied by black and white mothers were about equivalent as measured by the concentration index. With respect to income inequality, white mothers were more equally distributed across the 5 quintiles than were their black counterparts; furthermore, almost 70% of black mothers lived in the 2 least-equal quintiles of neighborhoods, in contrast to 35% of white mothers in the same quintiles. A similar pattern could be observed for poverty, with approximately 30% of white mothers but 75% of black mothers living in the 2 poorest quintiles. These racial differences at the neighborhood level suggest that neighborhoods should play a role in the acquisition of STDs during pregnancy.

Multilevel Logistic Regression Results

The results in Table 2 show the associations between neighborhood characteristics and the acquisition of STDs during pregnancy. Before including any independent variable, we test the intercept-only null models to confirm the appropriateness of using the multilevel models. The results support the use of multilevel models and indicate that a large proportion of the variance in STDs during pregnancy is explained by differences between neighborhood contexts (14.4%). Next, we include the residential segregation measures and cross-level interaction measures (model 1) and then examine income inequality and poverty index quintiles in model 2 and model 3, respectively. In our final model (model 4), all neighborhood characteristics are included.

Multilevel Logistic Regression Models Predicting the Acquisition of STDDP

Individual-level results are consistent across models; thus, we report the results from the final model (model 4). Ceteris paribus, the odds of acquiring STDs during pregnancy is 60% higher for non-Hispanic black women compared with non-Hispanic white women (odds ratio [OR], 1.60; 95% confidence interval [CI], 1.41–1.80). Maternal age is significantly associated with the odds of acquiring STDs during pregnancy: a 1-year increase in maternal age is associated with roughly an 8% decrease in the odds of acquiring STDs during pregnancy (0.92(1) × 1.00(1) ×(1) = 0.92). In addition, the odds of acquiring STDs during pregnancy are lower for married mothers than for unmarried mothers, and lower for mothers with relatively high educational attainment levels. Lastly, indicators for mothers’ socioeconomic status are significantly associated with the odds of acquiring STDs during pregnancy. Mothers who receive WIC benefits are about 12% (OR, 1.12; 95% CI, 1.04–1.20) more likely to have acquired STDs during pregnancy compared with mothers not receiving WIC benefits.

With respect to the neighborhood level covariates, our multilevel models show that neighborhood further explains a substantial proportion of individual-level variance in sexually transmitted diseases during pregnancy acquisition. Specifically, neighborhood residential segregation has both direct and indirect associations with women’s odds of acquiring STDs during pregnancy. The exposure dimension of racial segregation (ie, isolation index) is directly and positively associated with the odds of acquiring STDs during pregnancy. Model 1 shows that the odds of acquiring STDs during pregnancy increase by 2.5 times (OR, 2.47; 95% CI, 1.99–3.08) when isolation index increases by 1 unit. However, the dimension of concentration is not significantly associated with STDs during pregnancy. More importantly, the cross-level interaction between maternal race and isolation suggests that among black mothers, those who live in a more segregated neighborhood are less likely to have acquired STDs during pregnancy (OR, 0.56; 95% CI, 0.43–0.73) (model 2).

Figure 1 illustrates the predicted probabilities of acquiring STDs during pregnancy for non-Hispanic white and non-Hispanic black mothers across different levels of neighborhood isolation. Two findings are notable. First, the probability of acquiring STDs during pregnancy is consistently higher among non-Hispanic black mothers than their white counterparts; however, non-Hispanic white mothers were found to be more sensitive to neighborhood segregation. Specifically, when the level of neighborhood isolation increases from 0.1 to 0.7, the probability of acquiring STDs during pregnancy increases by almost 50% for non-Hispanic white mothers but 10% for non-Hispanic black mothers. Second, the black-white disparity in acquiring STDs during pregnancy is wider among racially mixed neighborhoods than racially segregated neighborhoods, which suggests that non-Hispanic black mothers may benefit from living with other co-ethics.

Figure 1
Figure 1:
Predicted probability of acquiring STDs during pregnancy by race/ethnicity across the isolation index values.

Neighborhood-level income inequality is also significantly associated with the odds of acquiring STDs during pregnancy. In model 2, comparing with the most equal quintile, the odds of acquiring STDs during pregnancy are 13% (OR, 1.13; 95% CI, 1.01–1.25) and 26% (OR, 1.26; 95% CI, 1.13–1.40) higher for women in the middle quintile and the least-equal quintile, respectively. Similarly, the poverty index shows that the odds of acquiring STDs during pregnancy are 18% (OR, 1.18; 95% CI, 1.05–1.33) and 45% (OR, 1.45; 95% CI, 1.29–1.63) higher for women residing in second-poorest and the poorest quintiles, respectively (model 3). When we examine racial segregation and income inequality simultaneously (model 4), both measures are still significantly associated with the odds of acquiring STDs during pregnancy, and patterns are consistent with previous models. However, the associations of structural inequality and absolute deprivation are attenuated. Specially, the association between income inequality and the odds of acquiring STDs during pregnancy are less salient.


The results of this study not only demonstrate the importance of accounting for neighborhood-level factors but also unveil the intertwined relationship between race/ethnicity and the acquisition of STDs during pregnancy. Segregation and income inequality are significantly associated with mothers' STDs during pregnancy acquisition above and beyond mothers’ individual characteristics. Our results are consistent with the places stratification hypothesis which posits that negative neighborhood conditions generated by individual and institutional discrimination against minority groups24 can adversely affect individuals' health.25–27 Residing in segregated neighborhoods is associated with higher odds of STDs during pregnancy acquisition through the direct pathway. However, the significant cross-level interaction terms further advance our understanding of how and why segregation matters. Our findings indicate that white mothers are more sensitive to neighborhood segregation than black mothers and that black mothers may in fact benefit from living with co-ethnics. These patterns are consistent with previous research finding that residing in segregated neighborhoods is associated with lower probability of maternal smoking during pregnancy for black mothers than for white mothers.27

For income inequality, we found that mothers who reside in neighborhoods with a high level of income inequality (relative measure of income distribution) and a high level of absolute deprivation (absolute measure of income distribution) have higher odds of acquiring STDs during pregnancy compared with mothers residing in more-equal and less-deprived neighborhoods. These results echo the previous research, which found that school-level structural inequality and absolute deprivation are associated with higher levels of STD acquisition for adolescents.22 In the final model, which accounted for residential segregation and income inequality jointly, we found that although the association of residential segregation remained salient, the associations of income inequality were attenuated. This finding is also consistent with previous ecological research finding that the effect of residential segregation on community-level gonorrhea rates was stronger than the effect of income inequality.16

This study has at least 4 limitations. First, because the data used in this study are cross-sectional, we cannot establish a causal relationship. To rule out the possibility of selection bias, future research should use longitudinal data to establish the causal relationships between neighborhood-level characteristics and the racial disparity in STDs during pregnancy acquisition. Second, several individual-level measures that may be associated with the racial disparity in STDs during pregnancy were not included because of data constraints, such as paternal information and maternal social connections. Third, our study focuses on black and white mothers in Pennsylvania, and it remains unclear whether our findings will be generalizable to other areas in the United States. It is plausible that residential segregation and income inequality may be associated differently in other places with different racial histories (eg, the South). Finally, the influence of neighborhoods may vary depending on how neighborhood is operationalized. Although using a census tract to define a neighborhood is a common practice in health research,18 future studies should be cautious of the modifiable areal unit problem,28 which refers to the possibility of producing different results when different scales or zones are used.29,30

The results of this study have important policy implications and lead to suggestions for future research. Our results demonstrate the importance of accounting for neighborhood-level factors, which we found to be significantly associated with STDs during pregnancy acquisition beyond mothers’ individual characteristics. This finding suggests that health policy makers aiming to prevent and reduce the prevalence of STDs during pregnancy and reduce the racial disparity in STDs during pregnancy should explicitly and carefully incorporate the notion of place in their policy design. Specifically, targeting neighborhoods with a high level of residential segregation may be beneficial in reaching more women at risk. In addition, targeting the most socioeconomically disadvantaged may yield most effectiveness in terms of reaching women at risk. Future studies should investigate the specific mechanisms by which neighborhood-level segregation and income inequality may influence STDs during pregnancy acquisition and the mechanisms by which racial disparity is generated (eg, lack of health infrastructure/resources and social disorganization). Elucidating the specific mechanisms will be crucial to designing more effective policies aimed at reducing the racial gap in STDs during pregnancy acquisition. In sum, eliminating racial health disparities in the United States is an important public health concern reflected by Healthy People 2020.1 To reduce the racial disparity in STDs during pregnancy, future research should take a more-nuanced approach by examining risk factors at multiple levels.


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