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Poverty matters: contextualizing the syndemic condition of psychological factors and newly diagnosed HIV infection in the United States

Oldenburg, Catherine E.a; Perez-Brumer, Amaya G.b; Reisner, Sari L.a,c

doi: 10.1097/QAD.0000000000000491
EPIDEMIOLOGY AND SOCIAL
Free
SDC

Background: Syndemic factors’, defined as co-occurring psychological conditions including major depressive disorder, substance and alcohol use, and intimate partner violence, have been shown to increase HIV incidence among MSM in the United States. However, this relationship has not been well characterized in the general population, particularly in the context of poverty.

Design: Prospective cohort study including a nationally-representative sample of 34 427 men and women in the National Epidemiologic Survey on Alcohol and Related Conditions wave 1 (2001–2002) and wave 2 (2004–2005).

Methods: Weighted multivariable logistic regression models were used to assess the association between syndemic factors and newly diagnosed HIV infection, and to assess how living below the poverty line (based on 2001 US Poverty Guidelines) modified this relationship.

Results: The proportion of participants reporting new HIV diagnosis in the past year was 0.22%, increasing from 0.19% among individuals with no syndemic factor to 5.1% among those with four syndemic factors. Adjusting for potentially confounding factors, each additional syndemic factor was associated with a 47% increase in odds of HIV infection [adjusted odds ratio (aOR) 1.47, 95% confidence interval (CI) 1.30–1.65]. The effect of syndemic factors was stronger among individuals living below federal poverty guidelines (aOR 1.96, 95% CI 1.57–2.44) compared to those living above poverty guidelines (aOR 1.21, 95% CI 1.07–1.36).

Conclusions: Among the US general population, the association between co-occurring syndemic factors and incident HIV infection was stronger in the setting of poverty. Mental health interventions, particularly in socioeconomically disadvantaged areas, should be considered to reduce transmission of HIV.

aDepartment of Epidemiology, Harvard School of Public Health, Boston, Massachusetts

bDepartment of Sociomedical Sciences, Columbia Mailman School of Public Health, New York

cThe Fenway Institute, Fenway Health, Boston, Massachusetts, USA.

Correspondence to Catherine E. Oldenburg, MPH, 677 Huntington Ave, 9th Floor, Boston, MA 02115, USA. Tel: +1 510 684 9466; e-mail: ceo242@mail.harvard.edu

Received 19 June, 2014

Revised 12 September, 2014

Accepted 16 September, 2014

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Introduction

In the United States, there were nearly 50 000 new cases of HIV per year in adults between 2006 and 2009 [1]. There are notable geographic differences in the distribution of HIV, with the largest burden of HIV in the southern United States [2,3]. Complex social forces, including socioeconomic factors and sex, are thought to contribute to the growing disparities in HIV incidence in the United States [4]. The HIV epidemic in the United States is considered a concentrated epidemic [5]. However, HIV prevalence among the Americans living in urban poor areas exceeds 2%, calling into question whether HIV should be considered a generalized epidemic in the setting of poverty [6]. Research has shown that poverty, above other social determinants such as sex, race/ethnicity, and sexual orientation, is the driver of the changing shape of the HIV epidemic today [6,7].

Multiple studies have demonstrated an association between psychological factors, including major depression, substance use, and experiences of violence, and HIV risk behavior [8–12]. These factors are thought to increase HIV risk by fueling HIV risk-taking behaviors, including increased engagement in unprotected sex and/or an increase in the number of partners or partner concurrency [13,14]. Although each risk factor may operate via separate pathways (e.g. through impaired decision making the ability to negotiate condom use), the co-occurrence of multiple psychological factors may further augment HIV risk-taking behavior. The co-occurrence of multiple, potentially interacting factors has been labeled as ‘syndemics’, and recognizes the crucial role of adverse social structures (e.g. poverty) in facilitating the clustering of health-related problems by person, place, or time [15]. As first proposed by Singer in 1994 [16], syndemics include both epidemics of disease and of the social conditions that independently and jointly contribute to adverse health. In relation to HIV, this recognizes that social inequality (e.g. poverty) plays a crucial role in the clustering of factors that facilitate HIV vulnerability, leading to the heightened potential for transmission and acquisition of HIV infection [15–18].

Facilitated by the upstream impact of social inequalities, this co-occurrence of factors is thought to lead to negative health consequences, including increased vulnerability for HIV infection [15,18,19]. For example, an increasing number of childhood adverse experiences (i.e. abuse or neglect, witnessing or experiencing violent crime, family or financial problems) have been shown to have a dose–response relationship with negative health outcomes [20]. With respect to HIV, a syndemic perspective has been readily employed to assess the disproportionate burden of the epidemic among inner city racial and sexual minority populations (e.g. urban poor populations of color) [16]. Although multiple studies have documented the importance of syndemics in HIV risk in key populations, particularly among MSM [13,19,21–23], a few studies have explicitly considered the role of syndemics on HIV incidence in the general population. Although it has been well established that the HIV epidemic in the United States disproportionately affects those living in poverty, a few studies have considered the role of poverty on the relationship between syndemic factors and HIV incidence.

To better understand how psychological and socio-economic factors affect HIV transmission risk according to the syndemic theory in the US general population, and to determine if poverty affects this association, we investigated relationships between major depressive disorder, substance use disorder, alcohol use disorder, and intimate partner violence (IPV), and self-reported newly diagnosed HIV infection. In addition, we applied a syndemic model as per Singer's [16] original proposed syndemic theory in 1994, and tested whether poverty moderated the association between syndemic psychological factors and HIV infection. We hypothesized that, in the context of poverty, the effect of syndemic conditions on newly diagnosed HIV infection would be exacerbated.

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Methods

Study sample

Data from wave 1 (2001–2002, N = 43 093) and wave 2 (2003–2004, N = 34 653) of the National Epidemiologic Survey on Alcohol and Related Disorders (NESARC) [24] were analyzed. The NESARC is a longitudinal, population-based, nationally representative epidemiologic study that investigates the prevalence of mental health conditions in the US general population among adults (over 18 years of age) who are noninstitutionalized. Non-Latino African Americans, Latinos, and individuals aged 18–24 years were oversampled; data were adjusted for oversampling, and weighted to represent the US general population based on the 2000 US census. Individuals interviewed in wave 1 were re-interviewed in wave 2. Individuals who were not followed up in wave 2 were more likely to live in poverty, be Latino, male, younger, less educated, unmarried, living in urban areas, southern, not have psychiatric disorders, and live in higher-cost-of-living states [25]. Complete methods for the NESARC have been previously reported in detail [24,26,27].

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Measures

Psychological syndemic factors

Potential syndemic factors included a diagnosis of major depressive disorder, substance use disorder (including amphetamines, opioids, sedatives, tranquilizers, cocaine, inhalants, hallucinogens, and/or heroin), and alcohol use disorder in the 12-month period prior to wave 1. Twelve-month major depressive disorder, substance use disorder, and alcohol use disorder were assessed using the Alcohol Use Disorder and Associated Disabilities Interview Schedule-IV (AUDADIS-IV) according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) definitions [28]. Because IPV data were not collected in wave 1, we included any IPV (physical and/or sexual) in the 12-month period prior to wave 2 as a syndemic factor. IPV was assessed through six questions, including: ‘How often did your spouse/partner push, grab or shove you’; ‘How often did your spouse/partner slap, kick, bite, or hit you’; ‘How often did your spouse/partner threaten you with a weapon like a knife or gun’; ‘How often did your spouse/partner cut or bruise you’; ‘How often did your spouse/partner force you to have sex with him/her’; and ‘How often did your spouse/partner injure you enough that you had to get medical care’ [29]. A response of more than never to any of the six questions was coded as having experienced IPV in the previous year. Individuals who reported not having a partner or dating during the year prior to wave 2 were coded as not experiencing IPV.

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Poverty

Living in poverty at wave 1 was coded using 2001 US Poverty Guidelines, and were based on household income and family size [25,30]. In the 48 continental United States, the poverty level was defined as [US$ 5570 + (number of persons in household) × US$ 3020], and individuals reporting a household income below this level were coded as living in poverty. For Alaska and Hawaii, slightly higher figures were used in accordance with the US Poverty Guidelines [30].

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Newly diagnosed HIV infection

Newly diagnosed HIV infection in the 12-month period prior to wave 2 was assessed with two questions: if the individual tested positive for HIV in the past year prior to the wave 2 interview and if a doctor confirmed the diagnosis. An affirmative response to both questions was coded as incident HIV infection. Individuals who reported ‘unknown’ if they had been diagnosed with HIV in the past year were coded as missing (N = 226) and not included in the analysis.

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Covariates

Several potentially confounding variables were included in all multivariable models. These variables were age, sex (female versus male), sexual identity (coded as identified as a sexual minority or no), race/ethnicity (categorized as White/Caucasian, Black/African American, Latino/a, or other, due to small numbers of incident HIV infections among Asian and American Indian ethnic groups), urbanicity [coded by metropolitan statistical areas (MSA) including living in the central city, outside central city, or not in an MSA], and educational attainment (coded as greater than high school or high school or less).

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Statistical analysis

Proportions for categorical variables and means and SDs for continuous variables were obtained for all variables included in multivariable analyses. Bivariate associations between each syndemic factor as well as poverty were obtained using a logistic regression model to assess relationships between each factor.

To test the relationship between syndemic factors and newly diagnosed HIV infection, first, a series of multivariable logistic regression models were used to assess the relationship between each syndemic factor individually and newly diagnosed HIV infection, adjusted for potentially confounding variables described previously. To test whether an increasing number of co-occurring syndemic factors was associated with a proportional increase in odds of newly diagnosed HIV infection, syndemic factors were added together to create a variable that reflected the number of co-occurring syndemic factors in the period prior to HIV diagnosis. A multivariable logistic regression model was used to assess the relationship between the number of syndemic factors and the newly diagnosed HIV infection.

Finally, we tested the effect of poverty on the relationship between the syndemic factors and the newly diagnosed HIV infection. Poverty was hypothesized to be a moderator of the relationship between syndemic factors and newly diagnosed HIV infection, and as such would affect the strength of the relationship between the two variables [31]. To test if poverty was a modifier of this association, a product term between poverty and syndemic factors was included in a multivariable logistic regression model, allowing identification of the effect of the syndemic term on newly diagnosed HIV infection in subgroups living above and below federal poverty guidelines. Secondary analyses restricting the sample to only men and only women were conducted to assess this relationship in men and women separately. All analyses were appropriately survey-weighted and conducted in Stata 13.1 (StataCorp, College Station, Texas, USA).

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Results

Table 1 presents characteristics of the study sample (N = 34 427), stratified by number of concurrent syndemic factors. The overall percentage of individuals reporting newly diagnosed HIV infection in the previous year was 0.22%, and it increased from 0.19% among individuals with no syndemic factors to 5.1% among individuals with four concurrent syndemic factors. Individuals living below the federal poverty guidelines in 2001 experienced a greater burden of syndemic factors. Table 2 shows bivariate associations between each syndemic factor. The only relationship that did not reach statistical significance was the relationship between alcohol use disorder and poverty.

Table 1

Table 1

Table 2

Table 2

Table 3 shows bivariate and multivariable associations between each syndemic factor individually and the newly diagnosed HIV infection, as well as bivariate and multivariable models modeling the additive effect of syndemic factors on newly diagnosed HIV infection. Other than the major depressive disorder, all syndemic factors were individually associated with HIV incidence, including substance use disorder [adjusted odds ratio (aOR) 3.71, 95% confidence interval (CI) 3.12–4.40], alcohol use disorder (aOR 1.31, 95% CI 1.16–1.47), and IPV (aOR 2.30, 95% CI 1.65–3.19), adjusting for potentially confounding factors. In the additive syndemic model, every additional syndemic factor was associated with a 47% increase in odds of HIV infection (aOR 1.47, 95% CI 1.30–1.65).

Table 3

Table 3

Table 4 displays results of a multivariable model assessing modification of the relationship between syndemic factors and newly diagnosed HIV infection by poverty status. Figure 1 graphically displays regression slopes for the additive effect of syndemic factors on probability of incident HIV infection among individuals living above compared to below poverty guidelines. Among individuals who lived below federal poverty guidelines, every additional syndemic factor was associated with a 96% increase in odds of incident HIV (aOR 1.96, 95% CI 1.57–2.44), compared to a 21% increase among individuals living above federal poverty guidelines (aOR 1.21, 95% CI 1.07–1.36). In an analysis stratifying by sex, the strongest association between syndemic factors and newly diagnosed HIV infection was among men who lived below the poverty line (aOR 4.15, 95% CI 2.71–6.37).

Table 4

Table 4

Fig. 1

Fig. 1

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Discussion

Our results indicate a significant association between comorbid psychological conditions, and partner violence and newly diagnosed HIV infection in the US general population, constituting a syndemic condition of psychological factors and HIV risk. The existence of a syndemic condition between psychological factors and both HIV risk and incident HIV infection has been well established among MSM [13,19,21,22]. Results of studies among MSM have consistently shown that odds of HIV and/or HIV risk are proportional to increasing numbers of syndemic factors [13,21,32,33]. The results of the present study indicate that there may be a similar relationship between syndemic factors and newly diagnosed HIV infection in the US general population, and that this relationship may be amplified in the setting of poverty.

Here, we found evidence that poverty is a modifier of the relationship between syndemic factors and newly diagnosed HIV infection. Among women, in particular, an increase in the number of syndemic conditions was only associated with HIV in the context of poverty, and among men, this relationship was considerably stronger in the context of poverty. Individuals of lower socio-economic status may be more likely to experience a greater number of co-occurring syndemic factors and thus have increased vulnerability to HIV infection. It is well established that the HIV epidemic in the United States is concentrated geographically in areas that are economically disadvantaged and among those living in poverty [3,34]. In the United States, lower socio-economic status has been described as both a risk factor for and a result of psychiatric disorders [35]. Conditions associated with living in poverty, such as crowding, underemployment, financial and other stress, and exposure to violence may increase the risk of one or more psychiatric disorders [36]. Moreover, IPV is differentially distributed and more prevalent in areas of lower socio-economic status, which could be due to chronic stress of poverty and/or sex inequality [37]. Guided by the syndemic theory, we recognize the importance of social context by assessing the association between syndemic factors, poverty, and HIV risk. Whereas the clustering of risk factors, or co-occurrence alone, is important, these results demonstrate that social inequality, here defined as poverty, modifies this relationship. These results suggest that poverty potentiates the association between these syndemic factors and HIV infection. For example, stress related to living in poverty could increase risk for psychiatric conditions, or exacerbate responses to syndemic factors in the form of increased HIV risk-taking behavior. Further work elucidating this pathway specifically will be important to understand how best to design interventions that address the heightened effect of syndemic factors in the setting of poverty.

The results of this study must be considered in the context of several limitations. HIV diagnoses were obtained via self-report, and HIV testing was not done as part of the NESARC study. This could introduce misclassification bias, especially in that to be diagnosed with HIV infection; one must be tested for HIV. A differential distribution in access to HIV testing access could therefore bias results. In the United States, there are disparities in access to HIV testing and care services with respect to poverty, urbanicity, and ethnic or racial background [38]. If individuals living below the poverty line or who had more syndemic factors were less likely to have been tested and thus know their result, there may be a downward bias in the study results. Similarly, individuals may not wish to disclose the HIV status, which could introduce bias. Future work should consider the effect of syndemics on biological assay-confirmed HIV incidence. However, this study represents one of the largest prospective studies that includes measures of newly diagnosed HIV infection with validated measures of psychiatric disorders, which gives this study the ability to consider not only the effect of syndemic factors but how they are modified by poverty. An additional limitation is that we were unable to control for sexual risk-taking behavior in this study, due to lack of assessment of recent HIV sexual risk behavior prior to the period on which HIV incidence was assessed. In addition, IPV was only assessed among participants who reported being in a relationship in the year prior to wave 2. It is possible that individuals experienced IPV outside of a relationship, which would not be captured here and thus could introduce misclassification. Poverty is only a single dimension of adverse social context. Although we believe this is a robust measure, it is possible that important dimensions of inequalities (i.e. stigma, security, neighborhood environment) are not captured by this analysis. Finally, given the relatively small number of new HIV diagnoses recorded in this study, we were unable to stratify more finely and assess the relationship between syndemic factors and specific subgroups of the population beyond those living in poverty. Future work should consider the moderating role of poverty on the relationship between syndemic factors and HIV incidence within specific subgroups, such as racial/ethnic minorities, in order to better understand how poverty affects this relationship.

The study provides additional evidence that co-occurring psychological and socio-economic conditions increase vulnerability to new HIV infection among the general population in the United States in a similar fashion as seen in MSM [13,21,22]. Importantly, this effect was considerably stronger among people living below federal poverty guidelines, and particularly among men living in the context of poverty. These results underscore that poverty is a key social determinant of health inequity and a core aspect of the syndemic theory [16]. We recommend that future analyses examine the association between co-occurring individual psychological factors and HIV infection explicitly consider and incorporate socio-economic factors, such as poverty.

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Acknowledgements

Author contributions: C.E.O. designed the study, conducted analyses, interpreted results, and drafted the manuscript. A.P.B. designed the study, interpreted results, and drafted the manuscript. S.L.R. designed the study, interpreted results, and drafted the manuscript. All authors critically reviewed and approved the final version of the manuscript.

Funding: C.E.O. was supported by a National Institute of Allergy and Infectious Disease T32 NRSA grant (T32AI007535; PI: Seage) and is currently supported by a National Institute of Drug Abuse T32 NRSA (T32DA0131911; PI: Flanigan). A.P.B. is supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development T32 HD049339 (PI: Nathanson) and the National Institutes of Mental Health R25 MH083620 (PI: Flanigan).

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Conflicts of interest

There are no conflicts of interest.

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References

1. Prejean J, Song R, Hernandez A, Ziebell R, Green T, Walker F, et al. Estimated HIV Incidence in the United States, 2006–2009. PLoS One 2011; 6:e17502.
2. Adimora AA, Ramirez C, Schoenbach VJ, Cohen MS. Policies and politics that promote HIV infection in the Southern United States. AIDS 2014; 28:1393–1397.
3. Nunn A, Yolken A, Cutler B, Trooskin S, Wilson P, Little S, et al. Geography should not be destiny: focusing HIV/AIDS implementation research and programs on microepidemics in US neighborhoods. Am J Public Health 2014. 775–780.
4. Aral SO, Adimora AA, Fenton KA. Understanding and responding to disparities in HIV and other sexually transmitted infections in African Americans. Lancet 2008; 372:337–340.
5. Campsmith ML, Rhodes P, Hall HI, Green T. HIV prevalence estimates: United States, 2006. MMWR Recomm Rep 2008; 57:1073–1076.
6. Denning P, DiNenno E. Communities in crisis: is there a generalized HIV epidemic in impoverished urban areas of the United States? AIDS 2010, Vienna, Austria, 18 -23 July 2010.States? AIDS 2010, Vienna, Austria, 18–23 July 2010.
7. Centers for Disease Control and Prevention. Characteristics associated with HIV infection among heterosexuals in urban areas with high AIDS prevalence: 24 cities, United States. MMWR Recomm Rep 2011; 60:1045–1049.
8. Armstrong G, Jorm AF, Samson L, Joubert L, Nuken A, Singh S, et al. Association of depression, anxiety, and suicidal ideation with high-risk behaviors among men who inject drugs in Delhi, India. J Acquir Immune Defic Syndr 2013; 64:502–510.
9. Reisner SL, Falb KL, Mimiaga MJ. Early life traumatic stressors and the mediating role of PTSD in incident HIV infection among US men, comparisons by sexual orientation and race/ethnicity: results from the NESARC, 2004–2005. J Acquir Immune Defic Syndr 2011; 57:340–350.
10. Bedoya CA, Mimiaga MJ, Beauchamp G, Donnell D, Mayer KH, Safren SA. Predictors of HIV transmission risk behavior and seroconversion among Latino men who have sex with men in project EXPLORE. AIDS Behav 2011; 16:608–617.
11. Mimiaga MJ, Noonan E, Donnell D, Safren SA, Koenen KC, Gortmaker S, et al. Childhood sexual abuse is highly associated with HIV risk-taking behavior and infection among MSM in the EXPLORE study. J Acquir Immune Defic Syndr 2009; 51:340–348.
12. Reisner S, Mimiaga M, Bland S, Skeer M, Cranston K, Isenberg D, et al. Problematic alcohol use and HIV risk among Black men who have sex with men in Massachusetts. AIDS Care 2010; 22:577–587.
13. Biello KB, Colby D, Closson E, Mimiaga MJ. The syndemic condition of psychosocial problems and HIV risk among male sex workers in Ho Chi Minh City, Vietnam. AIDS Behav 2014; 18:1264–1271.
14. Mimiaga MJ, Reisner SL, Pantalone DW, O’Cleirigh C, Mayer KH, Safren SA. A pilot trial of integrated behavioral activation and sexual risk reduction counseling for HIV-uninfected men who have sex with men abusing crystal methamphetamine. AIDS Patient Care STDs 2012; 26:681–693.
15. Singer MC, Clair S. Syndemics and public health: reconceptualizing disease in bio-social context. Med Anthropol Q 2004; 17:423–441.
16. Singer MC. AIDS and the health crisis of the U.S. urban poor; the perspective of critical medical anthropology. Soc Sci Med 1994; 39:931–948.
17. Singer MC. Introduction to syndemics: a systems approach to public and community health. San Francisco: Jossey-Bass; 2009.
18. Singer MC, Erickson PI, Badiane L, Diaz R, Ortiz D, Abraham T, et al. Syndemics, sex and the city: Understanding sexually transmitted diseases in social and cultural context. Soc Sci Med 2006; 63:2010–2021.
19. Stall R, Mills TC, Williamson J, Hart T, Greenwood G, Paul J, et al. Association of co-occurring psychosocial health problems and increased vulnerability to HIV/AIDS among urban men who have sex with men. Am J Public Health 2003; 93:939–942.
20. Mersky JP, Topitzes J, Reynolds AJ. Impacts of adverse childhood experiences on health, mental health, and substance use in early adulthood: a cohort study of an urban, minority sample in the U.S. Child Abuse Neglect 2013; 37:917–925.
21. Wim VB, Christiana N, Marie L. Syndemic and other risk factors for unprotected anal intercourse among an online sample of Belgian HIV negative men who have sex with men. AIDS Behav 2013; 18:50–58.
22. Santos GM, Do T, Beck J, Makofane K, Arreola S, Pyun T, et al. Syndemic conditions associated with increased HIV risk in a global sample of men who have sex with men. Sex Transm Infect 2014; 91:250–253.
23. Jie W, Ciyong L, Xueqing D, Hui W, Lingyao H. A syndemic of psychosocial problems places the MSM (men who have sex with men) population at greater risk of HIV infection. PLoS One 2012; 7:e32312.
24. Grant BF, Kaplan K. National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) Source and Accuracy Statement. Rockville, MD: National Institute on Alcohol Abuse and Alcoholism; 2005.
25. Thompson RG Jr, Wall MM, Greenstein E, Grant BF, Hasin DS. Substance-use disorders and poverty as prospective predictors of first-time homelessness in the United States. Am J Public Health 2013; 103:S282–S288.
26. Grant BF, Kaplan K, Shepard J. Source and accuracy statement for wave 1 of the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions. Bethesda, MD: National Institute on Alcohol Abuse and Alcoholism; 2003.
27. Grant BF, Stinson FS, Dawson DA, Chou P, Dufour MC, Compton W, et al. Prevalence and co-occurrence of substance use disorders and independent moodand anxiety disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry 2004; 61:807–816.
28. Grant BF, Harford TC, Dawson DA, Chou P, Pickering RP. The alcohol use disorder and associated disabilities interview schedule (AUDADIS): reliability of alcohol and drug modules in a general population sample. Drug Alcohol Depend 1995; 39:37–44.
29. Hahn JW, McCormick MC, Silverman JG, Robinson EB, Koenen KC. Examining the impact of disability status on intimate partner violence victimization in a population sample. J Interpers Violence. doi: 10.1177/0886260514534527.
30. Federal Communications Commission. Public Safety Communications. Fed Regist; 2001.
31. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986; 51:1173–1182.
32. O’Leary A, Jemmott JB, Stevens R, Rutledge SE, Icard LD. Optimism and education buffer the effects of syndemic conditions on HIV status among African American men who have sex with men. AIDS Behav. doi: 10.1007/s10461-014-0708-0.
33. O’Cleirigh C, Newcomb ME, Mayer KH, Skeer M, Traeger L, Safren SA. Moderate levels of depression predict sexual transmission risk in HIV-infected MSM: a longitudinal analysis of data from six sites involved in a ‘Prevention for Positives’ Study. AIDS Behav 2013; 17:1764–1769.
34. Buot M-LG, Docena JP, Ratemo BK, Bittner MJ, Burlew JT, Nuritdinov AR, et al. Beyond race and place: distal sociological determinants of HIV disparities. PLoS One 2014; 9:e91711.
35. Anakwenze U, Zuberi D. Mental health and poverty in the inner city. Health Social Work 2013; 38:147–157.
36. Cromley EK, Wilson-Genderson M, Pruchno RA. Neighborhood characteristics and depressive symptoms of older people: local spatial analyses. Soc Sci Med 2012; 75:2307–2316.
37. Tsai AC. Intimate partner violence and population mental health: why poverty and gender inequities matter. PLoS Med 2013; 10:1–3.
38. Penner M, Leone PA. Integration of testing for, prevention of, and access to treatment for HIV infection: state and local perspectives. Clin Infect Dis 2007; 45:S281–S286.
Keywords:

HIV; poverty; psychological; social determinants; syndemic

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