Racial segregation associated with new HIV infections among black heterosexuals living in the US

A greater degree of racial segregation in urban areas of the United States is associated with more new HIV infections among black heterosexual men and women, according to a study by Umedjon Ibragimov and colleagues, published in the Journal of Urban Health.

Results revealed that segregation was positively associated with HIV infection. The authors suggest that black/white socioeconomic inequalities in education, employment and poverty are mediators for this relationship. This study highlights the need to address racial segregation and structural racism as broader drivers of the HIV epidemic.

In 2016, according to the Centers for Disease Control and Prevention (CDC), HIV incidence in the US was 43.6 per 100,000 for black adults and adolescents as opposed to 5.2 per 100,000 for the white population. Literature on health disparities often cites segregation as a cause of the higher HIV burden in the black population and traces several pathways to explain this relationship. However, there are few empirical studies that directly investigate this relationship.

Glossary

multivariable analysis

Statistical technique often used to reduce the impact of confounding factors, in order to attempt to identify the real association between a factor of interest and an outcome. 

longitudinal study

A study in which information is collected on people over several weeks, months or years. People may be followed forward in time (a prospective study), or information may be collected on past events (a retrospective study).

confounding

Confounding exists if the true association between one factor (Factor A) and an outcome is obscured because there is a second factor (Factor B) which is associated with both Factor A and the outcome. Confounding is often a problem in observational studies when the characteristics of people in one group differ from the characteristics of people in another group. When confounding factors are known they can be measured and controlled for (see ‘multivariable analysis’), but some confounding factors are likely to be unknown or unmeasured. This can lead to biased results. Confounding is not usually a problem in randomised controlled trials. 

continuum of care

A model that outlines the steps of medical care that people living with HIV go through from initial diagnosis to achieving viral suppression, and shows the proportion of individuals living with HIV who are engaged at each stage. 

It is thought that segregation results in black and white households being separated into unequal neighbourhoods, with black families being disproportionately likely to live in neighbourhoods with multiple hazards (e.g. crime, exposure to illegal drugs and possible incarceration) and fewer resources (e.g. high-quality schools and housing).

Consequently, segregation often results in higher violent crime – with the US criminal justice system disproportionately incarcerating black men. This in turn leads to skewed sex ratios in black neighbourhoods. In these neighbourhoods, black heterosexual women have to choose from a smaller pool of available sexual partners, resulting in higher chances of establishing sexual relationships with men who are at a higher risk of having HIV. Socioeconomic inequality caused by segregation may also contribute to higher HIV risk via a combination of injecting drug use and transactional sex. Additionally, segregation may interfere with black residents accessing the HIV continuum of care as a result of limited geographic access to healthcare locally and prohibitive transportation costs to care that is further away.

This study looks at HIV incidence (new cases) in the heterosexual black population over eight years, and includes a multivariable analysis in order to isolate confounding variables and investigate possible mechanisms that link racial segregation to HIV infection. Racial segregation was measured using an isolation index for black residents in urban areas, while the investigated outcome was the incidence of HIV infections per 10,000 black adult heterosexuals.

The researchers also included a time lag of one year in their statistical analysis to account for the time needed between the exposure (racial segregation) and the outcome (HIV infection). While this study is strengthened by its longitudinal design, which is better able to assess causality, the authors recognise that one of the limitations is that it used a relatively short time period for analysis – they only considered the period 2008-2015, starting their analysis in 2007 to allow for the one year time lag.

The statistical analysis clearly indicates that baseline residential segregation and the rate of new HIV diagnoses are independently and positively associated. Thus, a 19% decrease in baseline isolation was associated with a 16.2% reduction in new HIV infections from 2008-2015.

The median black isolation index was 36.6% in 2007, indicating that, in half the geographical areas, black residents lived in a census area where more than a third of the residents were also black. This index remained relatively stable over time, with a 34.3% median in 2015. However, HIV diagnoses for black heterosexuals decreased by 37.5% over this time, indicating that change in isolation over time demonstrated weak positive association with the outcome. One possible explanation for this might be that changes in segregation during the relatively short study period were too small in magnitude to account for changes in the outcome.

In 2007, the median male to female sex ratio for black adults was 0.88 (88 men for every 100 women), indicating a relative deficit of black men in most areas. This remained relatively stable over the study period. However, the authors did not find any statistical evidence to suggest that skewed sex ratios in black neighbourhoods (as a result of possible incarceration of black men) was a mediating factor. However, they suggest that higher incarceration may not affect HIV rates via imbalanced sex ratios, but instead through destabilising social and sexual networks.

The authors say that the sizable positive association between racial segregation and new HIV infections indicates that it is a fundamental determinant of HIV for black heterosexual populations. However, to determine if this relationship is causal in nature (i.e. that segregation actually causes HIV infections), it is important to identify causal mechanisms that clearly link the two. Their statistical analysis suggested that the relationship between racial segregation and HIV diagnoses was mediated by factors such as rates of black educational attainment, racial inequalities in educational attainment and racial inequalities in poverty. For instance, there was a change of 51.4% noted in the association between segregation and HIV infection when the percentage of black adults with no high school diploma was added to the model. This is consistent with prior research showing higher HIV rates for black residents in areas with lower graduation rates.

Interestingly, based on the authors’ interpretation of the data, they suggest that while white/black inequality in terms of poverty may mediate the relationship between racial segregation and HIV infection, absolute poverty for black adults does not appear to play a mediating role. This highlights the important role specifically played by inequalities arising from racial disparities when it comes to HIV infection.

As suggested by the social science and public health literature, this study’s findings are consistent with the notion that segregation has harmful effects on health, particularly in terms of placing individuals at risk for HIV infection, and thus could be viewed as a fundamental cause of HIV infection in the US. This strengthens the argument for policy interventions that directly target social ills such as segregation and socioeconomic inequality as means of curbing new HIV infections.

References

Ibragimov U et al. Relationship of racial segregation to newly diagnosed cases of HIV among black heterosexuals in US metropolitan areas, 2008-2015. Journal of Urban Health, 2018. (Abstract).