Socioeconomic position (SEP) refers to the range of socioeconomic circumstances, such as income, education and occupation, by which individuals are hierarchically stratified in society [1]. Although it has been asserted that SEP may contribute to HIV prevalence and incidence in certain populations [2–5], empirical explorations of the SEP-HIV connection in developing countries have yielded equivocal results [6–9] and few such studies have been conducted in the US [10]. Nevertheless, some have advocated for the use of income-generating programs—the broad array of income, asset, education, and skill development activities intended to help families and individuals increase income and build assets—as HIV prevention tools in the US [11, 12]. Such programs may be particularly useful in light of the scale-up and replication challenges surrounding HIV behavioral interventions [13, 14]. However, it is yet to be determined whether these programs can be sustainably effective with respect to economic development and HIV prevention. If income-generating programs do not result in reductions in HIV—either due to the challenges of blended objectives, or because of a lack of relationship between SEP and HIV—the potential exists for political and social backlash to activities that may otherwise be beneficial in their own right. The present study is one attempt to explore the relationship between SEP and HIV.

Several theories have been offered to explain the potential link between SEP and HIV [15–20]. First, poverty, low income and economic hardship have been identified as influencing the psychological well-being of persons through their effects on psychological distress and depression [16, 21–24]. Although there is little evidence that negative affective moods and depression are directly related to sexual behavior [25, 26], they are positively correlated with substance use [27–29], which in turn is associated with increased HIV risk-related behavior [30–32]. Additionally, chronic stressful events and depression have been linked to weakened immunity [23], which may lead to increased susceptibility to HIV infection [33].

Second, lower SEP may constrict an individual’s capability—the set of alternative ways of being and doing [34–36]. This has been extensively discussed with respect to female empowerment and HIV [37–39], with a focus on women’s ability to ensure their partners’ condom use [40]. Poverty and lower income are also likely to constrain livelihood options—the financial means whereby one lives [41]. For some women and men this may necessitate the exchange of sex for material or economic gain. Exchange sex is a key determinant in HIV-related risk behavior among men and women [42, 43].

Third, owing to the intersection of race and class in the US, and the concomitant factors of racism, classism and residential segregation, persons with different incomes are likely members of substantially different social and sexual networks [4, 44, 45]. Network effects are considered to be important to the transmission and acquisition of HIV and STIs both independent of behavior and due to their effect on sexual behavior [5, 20, 46–49]. Theoretically, the same sexual behaviors (e.g., unprotected intercourse) can have vastly different consequences depending on the prevalence of HIV within a sexual network and number of overlapping partners [50, 51]. Additionally, the high rates of incarceration among lower income men and women, particularly African Americans, may exert a strong influence on marital ties, marriage formation and concurrency (having multiple overlapping sexual partners) [4, 5].

Economic interventions are likely to be of limited benefit to HIV prevention unless they are able to address the relevant individual, social and structural factors that influence behavior and transmission. At best, however, most economic interventions will improve an individual’s socioeconomic factors (e.g., income) at the margins. Economic intervention participants are more likely to transition from ‘poor’ to ‘less poor’ than from ‘poor’ to ‘rich.’ Thus, we assessed whether associations between marginal differences in SEP and HIV risk-related behavior were evident among a group of predominantly lower-income heterosexuals in San Francisco. We explored four risk-related behaviors that are relevant to the theories outlined above: unprotected vaginal intercourse (UVI), substance use during UVI, concurrency, and exchange sex.

The sample consisted of 164 men and 286 women. The majority of respondents reported never having been married: 78% of men and 77% of women. Only 8% of men and 6% of women reported being currently married. The majority of respondents were black (over 80% of men and women). The sample was predominately lower-income although displaying a range of SEP characteristics. In 2007, the median household income in San Francisco County was $67,333 and approximately 11% of residents had a household income below the Federal Poverty Line (which was $10,210 for a single adult). Within our sample, 45% of men and 55% of women reported household income below $10,000, and 18 and 12% of men and women, respectively, reported an income above $30,000. Roughly 42% of men and 38% of women reported full or part time employment, and 49 and 48% of men and women, respectively, reported being unemployed or homemakers. Most (76% of men and 73% of women) respondents resided in HRAs. The distribution of education was similar across sexes: 21% reported having less than a high school degree, 48% had a high school diploma or GED, and 31% had at least some postsecondary education.

In general, none of our measures of socioeconomic position—household income, per capita income and employment status—produced significant results for any of the HIV risk-relevant measures. With respect to total UVI partners in the prior 12 months, men reported a mean of four and women reported a mean of five. As evident in Fig. 1, the mean values are substantially influenced by the presence of outliers for both men and women. Men and women reported a median of two UVI partners in a 12 month period. The incidence rate ratio (IRR) for the mean number of partners (our inferential model) was roughly one regardless of income, per capita income, or employment status for both men and women (Table 1). Exceptions were evident among male respondents when income categories were used. Although the pattern is suggestive of a modest gradient decline in UVI partners as income increases the only significant income effect was evident for men with an annual income of $15,000–$29,000 compared to men with income less than $5,000 (IRR 0.52, P < .01). For both men and women respondents who identified as having ‘other’ employment had significantly higher rates of UVI partners compared to employed persons (IRR 2.0, P < .05) (‘Other’ employment respondents are those who were students or did not consider themselves employed, unemployed or a homemaker. Disabled and retired persons were excluded.). Owing to lack of significant findings, we do not present relative risk tables for subsequent analyses.Fig. 1

Distribution of total UVI partners in 12 months among respondents, by sex and marital status. Note: Values in parentheses reflect the total number of respondents. Boxes represent the interquartile range, and the dark horizontal line indicates the median

Advocacy of income-generating programs as HIV prevention tools must be grounded on evidence of potential effectiveness, sustainability and a connection between economic circumstances and HIV risk. The goal of the present study was to assess whether evidence of an association between SEP and HIV risk-relevant behaviors could be identified in a cross-sectional observational study of lower-income heterosexuals. In general, we found no evidence of a direct association for either men or women. The case for an association between poverty and HIV is typically grounded on the basis of regional or racial/ethnic associations [12]. Our lack of significant findings here may support, rather than refute this conception of an SEP-HIV link. Respondents in the sample tended to reside in the same geographic areas within San Francisco, which are the poorest areas of the city. The contextual effect of neighborhood economic circumstances may be more important to HIV risk than individual economic status. Thus, income generating programs that target individuals may be less effective than programs that target community economic development. Alternatively, the absence of a demonstrated association between residence in the geographically bound HRAs and the five measures of risk-relevant behavior would suggest that social/sexual networks may be a more important focus for HIV prevention than geographic targeting alone.

To our knowledge, this is the first study to assess individual economic circumstances and HIV risk-relevant behavior among almost exclusively lower income heterosexuals in the US. We should note that the data used here were drawn from a non-probability sample, which is likely not fully representative of the heterosexual population in San Francisco’s HRAs. Moreover, the focus on HRAs precludes our ability to assess community economic context as a determinant of HIV risk-relevant behaviors. Additional studies encompassing more diverse geographic and household populations are necessary in determining how structural factors such as SEP may contribute to HIV risk among heterosexuals. Notably, heterosexual transmission constitutes a smaller proportion of AIDS cases in the West compared to the South and Northeast regions of the country [56], and regions differ substantially with respect to the socioeconomic contexts they, their states and rural and urban areas face [57]. Consequently, associations between SEP and HIV are likely to differ across geographic and residential characteristics.

HIV transmission in sexual partnerships is a function of exposure, infectivity and susceptibility. We have addressed the potential influence of SEP on behaviors relevant to HIV exposure. The study is limited by the restricted and blunt definitions of SEP, and by the inability to address structural factors such as segregation and networks that may be relevant to exposure. Other studies should also examine whether SEP is associated with differences in infectivity and susceptibility among lower income heterosexuals. Factors such as material hardship and health care access may be important determinants of differentials in infectivity and susceptibility. Future studies that better account for the complexity of both SEP and HIV risk, and that are designed to provide comparative analyses of the role of contextual differences will be best suited for exploring potential associations between SEP and HIV among lower-income heterosexuals.

Although we were unable to identify a consistent or significant relationship between SEP and risk-relevant behavior, we do not conclude from these findings that economic interventions will not influence HIV risk. In the absence of a direct SEP-HIV link, economic interventions may influence other proximal factors to HIV risk such as self-efficacy and agency. Given the dearth of studies addressing the topic of SEP and HIV, however, it is difficult to make a case for or against economic interventions as HIV prevention tools. Further investigation of the SEP-HIV link is warranted. Studies should utilize broader SEP measures and move beyond sexual behavior to incorporate other factors relevant to HIV exposure, infectivity and susceptibility among lower-income heterosexuals. Use of household or venue-based probability sampling will improve sample and network diversity and better support population-level inference. Multisite observational studies can exploit residential and temporal differences in local-level economic circumstances to approximate a ‘natural experiment’ better capable of providing comparative data on the potential SEP-HIV link. Such research will provide an important foundation for development and implementation of effective policies and programs to reduce heterosexual HIV transmission in the US.