Neighborhoods and HIV: A Social Ecological Approach to Prevention and Care

Abstract

Neighborhood factors have been linked to HIV risk behaviors, HIV counseling and testing, and HIV medical care. However, the social–psychological mechanisms that connect neighborhood factors to HIV-related behaviors have not been fully determined. In this paper we review the research on neighborhood factors and HIV-related behaviors, approaches to measuring neighborhoods, and mechanism that may help to explain how the physical and social environment within neighborhoods may lead to HIV related behaviors. We then discuss organizational, geographic, and social network approaches to intervene in neighborhoods to reduce HIV transmission and facilitate HIV medical care with the goal of reducing morbidity and mortality and increasing social and psychological well-being.

Researchers and practitioners have produced a wealth of information on individual-level factors associated with HIV risk behaviors, testing, and medical care. In parallel, studies on neighborhood factors and health have burgeoned. There is a wealth of studies that find HIV risk behaviors and HIV rates are linked with neighborhood characteristics. Studies have also linked HIV testing and HIV medical care to neighborhood factors. These neighborhood effects may be amenable to intervention; however, the mechanisms that connect neighborhood factors to HIV-related behaviors have not been fully determined. While it has been established that HIV related behaviors are geographically clustered, there is substantial debate on the best way to intervene in neighborhoods to reduce HIV transmission and facilitate HIV medical care with the goal of reducing morbidity and mortality.

In this paper we review the research on neighborhood factors and HIV risk behavior. We first examine the literature on neighborhoods and HIV-related behaviors. Then we examine approaches to measuring neighborhoods. Next we discuss theories on mechanisms that help to explain how the physical and social environment within neighborhoods may foster HIV transmission and impede HIV care. Finally, we consider how this literature informs potential intervention approaches to HIV prevention and care, as well as training needed to equip investigators and communities with skills necessary to study and change geographically based HIV risk behaviors.

The field of neighborhood factors and HIV has burgeoned over the last two decades. Much of this growth can be attributed to technological and statistical advances. Geographic information systems (GIS) software allows for the easy mapping of specific locations, such as a residential address, health care facility, needle exchange site, as well as the mapping of broader geographic areas such as census blocks, neighborhoods, and zip codes (Rushton, 2003; Vine, Degnan, & Hanchette, 1997). There are now a multitude of data sets of geographic areas such as census data (e.g., crowding, unemployment, income, age distribution, and rental properties), 911 calls, police arrests (include type of crime and age of the arrestee), liquor store density, and other zoning and urban planning datasets that can be linked to HIV related behaviors at both the individual and neighborhood level (Freudenberg, Fahs, Galea, & Greenberg, 2006). In addition to GIS software, there are numerous multilevel statistical analyses approaches for simultaneously modeling individual and neighborhood factors and software that are readily accessible to researchers.

Neighborhoods and modes of transmission

Neighborhood disadvantage has been strongly linked to injection drug and heterosexual risk behaviors and transmission patterns. Both main effects and interactions with individual-level factors have been reported (Bauermeister, Zimmerman, & Caldwell, 2011; Braine et al., 2008; Burns & Snow, 2012; Friedman et al., 2007a; Fuller et al., 2005; Généreux, Bruneau, & Daniel, 2010; Johns, Bauermeister, & Zimmerman, 2010; Kerrigan, Witt, Glass, Chung, & Ellen, 2006; Latkin, Williams, Wang, & Curry, 2005; C. A. Latkin, Curry, Hua, & Davey, 2007; Maas et al., 2007; Parrado & Flippen, 2010; Schroeder et al., 2001; Zamani et al., 2010). Neighborhood factors have also been linked to HIV mortality (Arnold, Hsu, Pipkin, McFarland, & Rutherford, 2009; Joy et al., 2008), and testing (Mashburn, Peterson, Bakeman, Miller, & Clark, 2004). HIV risk behavior clustering by neighborhood may exacerbate the potential of geographically bound HIV transmission, particularly in areas with heightened HIV prevalence.

HIV transmission among men who have sex with men (MSM) also may have dynamics associated with neighborhood factors (Egan et al., 2011; Frye et al., 2010; Kelly, Carpiano, Easterbrook, & Parsons, 2012; Wiewel, Hanna, Begier, & Torian, 2011), but these are more likely to differ by city and geographic region as compared to injection drug and heterosexual transmission. Some cities have neighborhoods that are perceived to be supportive of MSM or having a strong MSM place identity. These areas may have targeted prevention activities but they may also have high risk venues and higher rates of HIV, which may lead to greater HIV transmission risk as compared to other geographic areas.

Toxic Neighborhoods

Neighborhoods that have high rates of HIV linked to injection drug user (IDU) and heterosexual transmission often suffer from a range of correlated afflictions which have been conceptualized as “toxic” (Furr-Holden, Milam, Reynolds, Macpherson, & Lejuez, 2012). These conditions include high levels of violence, poor housing stock, low levels of employment, poor schools, high dropout rates, and high levels of drug dealing and use. MSM HIV transmission is also not immune to the same poor neighborhood conditions that may lead to IDU and heterosexual transmission.

In many urban neighborhoods factors such as level of unemployment, abandoned buildings, level of poverty, and level of violent crime are often highly correlated, which makes it difficult to isolate independent mechanisms that promote HIV transmission. The theoretical notion of overlapping epidemics or syndemics (Singer et al., 2006) can also be viewed as a neighborhood-level phenomenon; that is, neighborhoods are the syndemics. Given the high correlation among many neighborhood indicators, it is important to utilize theoretical approaches to help us disentangle these associations and conduct empirical analyses of the links between neighborhood factors and HIV. Moreover, most often these studies are from neighborhoods in only one jurisdiction. Consequently, we do not know whether the same factors have the same influence in other places. In order to adequately understand and intervene on neighborhood factors linked to HIV it is important to measure key neighborhood characteristics.

Measuring neighborhoods

In order to adequately understand and intervene in neighborhoods it is critical to accurately measure key neighborhood factors. Community and environmental psychology has a long history of developing and validating scales of neighborhoods and communities (These measures have often focused on assessing dimensions of sense of community and community resources) (Long & Perkins, 2003; Peterson et al., 2008; Townley & Kloos, 2009). Boundaries of neighborhoods have psychological dimensions as well as physical dimensions, which may be determined subjectively as well as objectively. There are three major approaches to measuring neighborhood characteristics: self-reports, observations, and geographically based datasets (Weiss, Ompad, Galea, & Vlahov, 2007).

Self-reported measures

A variety of researchers have examined neighborhood characteristics using the most evident strategy: by asking residents to describe their neighborhood. One benefit of this approach is that it can allow residents to define and characterize their own sense of neighborhood boundaries as well as the experienced frequency of specific events or occurrences (Basta, Richmond, & Wiebe, 2010). They can also describe the extent to which they believe events or neighborhood conditions are problematic or stressful. These same benefits, however, may also lead to implicit bias. Residents’ experiences of their neighborhoods are shaped by their own personal characteristics, as well as their patterns of daily life and socialization (Latkin, German, Hua, & Curry, 2009; Takahashi, Wiebe, & Rodriguez, 2001). Thus, some neighborhood residents may witness greater levels of disorder, benefit less from community cohesion, and experience more stress from these aspects than other residents, while others’ fears may exacerbate their perceptions of disorder and crime levels (Sampson & Raudenbush, 1999). Others may be unaware of neighborhood qualities that have a major impact on HIV, such as nearby syringe access, late night commercial sex venues, sex partner meeting locations, condom access, or drugs available on a particular corner. Several studies have found that self-reported measures of neighborhood factors, especially social disorder, are associated with both sexual and drug related HIV risk behaviors (Kerrigan, Witt, Glass, Chung, & Ellen, 2006; Latkin, Williams, Wang, & Curry, 2005; Latkin, Curry, Hua, & Davey, 2007; Rudolph, Linton, Dyer, & Latkin, 2012; Theall, Sterk, & Elifson, 2009).

Observer measures

Several groups of investigators have used observational methods to rate neighborhoods. Researchers have used direct observations of neighborhoods or videographed neighborhoods and then coded them (Schaefer-McDaniel, Caughy, O’Campo, & Gearey, 2010; Shareck, Dassa, & Frohlich, 2012). Some researchers have begun coding Google map images of neighborhoods and other online tools (Badland, Opit, Witten, Kearns, & Mavoa, 2010; Clarke, Ailshire, Melendez, Bader, & Morenoff, 2010; Rundle, Bader, Richards, Neckerman, & Teitler, 2011). Perkins and Taylor (1992; 1996) were one of the first investigators to compare objective and subjective measures of neighborhoods. Sampson and Raudenbush (1999) demonstrated how these data could be used to estimate two distinct “latent” constructs, physical disorder and social disorder. These rates provide assessments that are independent of the perceptions of those who live in the neighborhoods but may be time consuming and miss aspects of the neighborhoods that have an important impact on HIV and other health behaviors. For example, most observational measures do not record the inside of households, which may have factors such as peeling paint, poor heating and ventilation, and crowding. There also may be factors which are not static and hence are difficult to assess through brief observations but nevertheless contribute to high levels of stress such as rats or drug markets which tend to move locations over time due to policing practices.

Geographically based datasets

There is a wide array of public and commercial geographic databases. The census data is a very rich source of neighborhood data and can provide insight into the social and environmental context of individuals. Numerous studies have used census and other public data sets to examine how such neighborhood factors may be linked to HIV risk behaviors (Arnold, Hsu, Pipkin, McFarland, & Rutherford, 2009; Gindi et al., 2011a; Weiss, Ompad, Galea, & Vlahov, 2007; Williams & Latkin, 2007). City health and planning departments and other governmental organizations often collect data that is either geographically linked or can be manipulated to be compatible to GIS software. In addition, most GIS software providers sell maps with vast amounts of geographic data. However, one challenge with linking geographic databases is that they are not all based on the same geographic areas. Some may be census blocks, while others are neighborhoods or zip codes. Given the wide range of possible neighborhood variables to measure it is important to focus these measures based on theoretical considerations.

Theories on neighborhood influence on HIV and related health behaviors

Neighborhoods can be conceptualized as having neighborhood level social characteristics such as levels of social capital, collective efficacy, social disorganization, and stress, in addition to their physical features and geographic access to resources (Galea & Vlahov, 2005). Neighborhoods may also reflect aggregate individual level attributes of community residents. On an individual level, HIV risk behaviors have been associated with depression (Fendrich, Avci, Johnson, & Mackesy-Amiti, 2013; Klein, Elifson, & Sterk, 2008; Lennon, Huedo-Medina, Gerwien, & Johnson, 2012; Mandell, Kim, Latkin, & Suh, 1999; Stein, Solomon, Herman, Anderson, & Miller, 2003), substance abuse (Booth, Des Jarlais, & Friedman, 2009; Celentano, Latimore, & Mehta, 2008; Miller, 2003), low education (Clark, Kissinger, Bedimo, Dunn, & Albertin, 1997; Miller & Neaigus, 2002; Mimiaga et al., 2009; Strathdee et al., 1998), and homelessness (Aidala, Cross, Stall, Harre, & Sumartojo, 2005; Kidder, Wolitski, Pals, & Campsmith, 2008). These individual level factors have all been linked to neighborhood level factors. Given the interrelation among these psychosocial conditions, it is useful to consider what social organizations and systems within neighborhoods may alleviate these conditions to help reduce HIV transmission and facilitate HIV testing and care. In the following section we review key theoretical constructs that may help to explain the relationship between neighborhood factors and HIV-related behaviors.

Risk environment

Neighborhoods are characterized by physical and social environments and their interactions. A recent focus in HIV prevention has been on the risk environment, which has been defined “as the space – whether social or physical – in which a variety of factors interact to increase the chances of harm occurring” (T. Rhodes, 2009 pg 193). This construct overlaps with the concept of behavioral setting, emphasizing how physical environments influence behaviors. The notion of behavioral setting has a rich tradition in psychology stemming from the work of Barker (1968). The concept of risk environments differs from behavioral settings with greater emphasis on multiple levels and less emphasis on micro-social settings. The literature on behavioral settings has emphasized that there are a set of expectations, roles, and behaviors that are strongly linked to settings. One type of behavioral setting is a bar. Bars have been found to be key locations for meeting new partners, transactional sex, and locations in which alcohol may facilitate sexual risk (Grov, Hirshfield, Remien, Humberstone, & Chiasson, 2011; Kalichman, Simbayi, Cain, & Jooste, 2007; Sherman, Lilleston, & Reuben, 2011; Watt et al., 2012). Bars have also been identified as an important loci for HIV prevention interventions (Sandoy, Siziya, & Fylkesnes, 2008), including the early classic community opinion leader studies by Kelly and colleagues (1991). One intervention approach has been to train bartenders in skills to refuse to serve inebriated customers. However, this approach has met with mixed success (Warpenius, Holmila, & Mustonen, 2010). Although the study of behavioral settings is an important chapter in the history of psychology, it never burgeoned into a large area of study. It is likely that this is due in part to the time commitment needed to observe and document behavioral settings as well as the descriptive nature of these studies. Despite the fact that it has been documented that settings such as bars, shooting galleries, and sex exchange venues are linked to HIV risk behaviors (Drumright & Frost, 2010; Reisner et al., 2009; Rietmeijer, Wolitski, Fishbein, Corby, & Cohn, 1998; Strathdee et al., 2001) few studies have developed typologies or other strategies for assessing the setting-specific characteristics that may influence HIV transmission and appropriate interventions based on these characteristics.

Neighborhood disorder

Many impoverished urban inner city neighborhoods in the US suffer from physical signs of decay such as abandoned buildings, litter, and graffiti. Neighborhood social disorder theory links physical signs of decay and neglect within a neighborhood to concentrated social and health consequences (Chappell, Monk-Turner, & Payne, 2011; Markowitz, Bellair, Liska, & Liu, 2001). For those who live in circumstances of persistent disorder, these physical signs may be visible reminders of a dissatisfying living situation. They may also further exacerbate feelings of entrapment and fear among those whose economic or social circumstances will not allow residential mobility (Wilson, 1987). In these ways, perceptions of physical disorder can contribute to psychological distress (Curry, Latkin, & Davey-Rothwell, 2008; Ewart & Suchday, 2002; Steptoe & Feldman, 2001), which in turn is strongly linked to HIV risk behavior. Additionally, neighborhood disorder is associated with high crime, drug markets, and sex exchange venues, all of which can foster circumstances of risk and further shape perceptions of one’s environment (Sampson, Raudenbush, & Earls, 1997). In a series of studies, investigators discovered that a neighborhood’s level of physical disorder, as rated by outside observers, is linked to fear of crime (Perkins, Meeks, & Taylor, 1992; Perkins & Taylor, 1996). Researchers have also linked fear of crime to neighborhood level social disorder such as loitering, public drunkenness, litter, vandalism, and the number of vacant houses (LaGrange, Ferraro, & Supancic, 1992; Lewis & Maxfield, 1980; Perkins & Taylor, 1996). It has been theorized that in some disadvantaged neighborhoods with restricted resources and opportunities, there exist high levels of social disorganization, and in such neighborhoods, social control mechanisms are unavailable or insufficient to control deleterious behavior (Lewis & Salem, 1981; Skogan, 1990). Although the issue of crime and fear of crime has been the focus of much of the discourse on social disorganization, there are several cross-sectional studies that have examined the relationship between social disorder and HIV risk behaviors (Latkin, Williams, Wang, & Curry, 2005; Latkin, Curry, Hua, & Davey, 2007). These cross-sectional studies find a consistent association between social disorder and HIV risk behaviors among inner-city substance using populations.

Collective efficacy

Collective efficacy is another theoretical perspective that is based on neighborhood factors (Sampson, Raudenbush, & Earls, 1997). It refers to the shared willingness of neighbors to maintain a level of social control that is implicitly and jointly agreed upon. It requires shared expectations, engagement, and trust among community residents, such that neighbors can come to rely upon each other to respond to specific aggrievances. For example, can neighbors expect that other neighbors would object to corner drug dealing? or to kids cutting school? or to infrastructure problems such as potholes or insufficient lighting? The two key hypothesized domains of collective efficacy are informal social control, which assesses the ability of neighborhoods to induce public order and obtain resources from the community, and social cohesion, which involves neighbors knowing, helping, and trusting each other. Collective efficacy tends to be lower in neighborhoods of high poverty and low home ownership (Sampson & Morenoff, 2004), reflecting some of the structural origins of trust and community engagement. However, it is also true that collective efficacy has been shown to mediate associations between concentrated disadvantage and negative outcomes (Sampson, Raudenbush, & Earls, 1997). Several studies have found that social cohesion is associated with lower HIV risk behaviors, and collective efficacy interventions have been utilized as an approach for structural interventions for violence control and for HIV prevention (Carlson, Brennan, & Earls, 2012).

Perceived neighborhood cohesion has been associated with condom use (Kerrigan, Witt, Glass, Chung, & Ellen, 2006; Lang et al., 2011). However, interventions to enhance collective efficacy may be challenging as neighborhoods with low collective efficacy may be difficult to organize. Other macro-level factors such as low resources due to unemployment may impact the ability of neighborhoods to organize community-based HIV prevention and care initiatives (Cornish & Campbell, 2009).

Social capital

A large body of research has examined the relationship between social capital and HIV-related behaviors (Campbell, Williams, & Gilgen, 2002; Crosby, Holtgrave, DiClemente, Wingood, & Gayle, 2003; Holtgrave & Crosby, 2003; Pronyk et al., 2008; Takahashi & Magalong, 2008). Theories of social capital emphasize access to resources and norms of behavior that are located external to any one individual (Kawachi, 1999). Social capital has been conceptualized as networks through which resources flow (Son & Lin, 2008). Within a neighborhood, social capital may exist on an individual or collective level. On an individual level, any one neighbor can draw on other neighbors for specific resources, such as borrowing a ladder or how to call the city about a trash problem. On a collective level, neighbors can draw on the power they have as a group to gain access to resources that may be more challenging for an individual to acquire. This may translate into political power or other involvement in community oriented local governance. Social capital may also be conceptualized as organizations, which are often geographically based, such as schools, libraries, and community-based organizations, that may function cohesively to achieve goals. Social capital has included neighborhood level factors in some assessments. In the context of HIV, social capital has been conceptualized as a mechanism for community response to social marginalization. A range of studies have found that low social capital is linked to substance use (Reynoso-Vallejo, 2011; Rogers, Ramaswamy, Cheng, Richter, & Kelly, 2012; Winstanley et al., 2008; Wray-Lake et al., 2012), but mixed findings on the associations of HIV serostatus and social capital have also been reported (Campbell, Williams, & Gilgen, 2002; Pronyk et al., 2008; Takahashi & Magalong, 2008). The mechanisms involved in these associations remain unclear (Friedman et al., 2007a; Reynoso-Vallejo, 2011). Interventions have successfully strengthened social capital among communities with high rates of HIV (Campbell & Mzaidume, 2001; Fullilove, Green, & Fullilove, 2000; Pronyk et al., 2006). A more psychological perspective on risk is boredom, which has been linked to HIV risk behaviors (German & Latkin, 2012), and may be connected to a lack of organizational involvement and opportunities for engagement with others. Moreover, research suggests that a lack of neighborhood activities is linked to greater adolescent sexual behavior (Akers, Muhammad, & Corbie-Smith, 2011).

Stress

It is well documented that neighborhoods sharply differ on level and type of stressors (Morello-Frosch, Zuk, Jerrett, Shamasunder, & Kyle, 2011; Wallis, Winch, & O’Campo, 2010). Stress predicts depressive symptoms, which have been also linked to sexual and drug related HIV risk behaviors (Latkin, Williams, Wang, & Curry, 2005; Latkin, Curry, Hua, & Davey, 2007). Neighborhoods with high levels of poverty, which is linked to HIV rates, are more likely to have stressors of violence, gangs, poor housing stock, lack of greenery, pollution, noise, and crowding, as compared to more affluent neighborhoods (Evans III, 1994). Another potential neighborhood stressor is poor treatment by police, which has been reported by drug users and non users in impoverished neighborhoods (Cooper, Moore, Gruskin, & Krieger, 2004). Several studies have also found that perceived stress is associated with anxiety and depression among people living with HIV/AIDS (Kang, Mellins, Dolezal, Elkington, & Abrams, 2011) and also with lower levels of Highly Active Antiretroviral Therapy (HAART) adherence (Blashill, Perry, & Safren, 2011). Among MSM stress due to homophobia has been well documented, yet there is little literature on how neighborhood factors may buffer or exasperate homophobia.

Neighborhood resilience

Although the construct of resilience has traditionally focused on individual level and family factors, it recently has been applied to neighborhoods and communities (Cairns, Curtis, & Bambra, 2012; Maggi, Roberts, MacLennan, & D’Angiulli, 2011; Okvat & Zautra, 2011; Pearson, Pearce, & Kingham, 2012). Important neighborhood resilience research questions include delineating the social and physical resilience factors in disadvantaged neighborhoods that may help to prevent the spread of HIV. There also may be neighborhood level resilience factors that facilitate material and emotional support for people who are living with HIV, sexual minorities, drug users, and other at risk populations.

Opportunities for high risk behavior

Availability of illicit substances, alcohol, and commercial sex differ markedly by neighborhood (Parrado & Flippen, 2010; Scribner, Theall, Simonsen, & Robinson, 2010) and open air drug markets tend to be concentrated within inner-city neighborhoods (Draus, Roddy, & Greenwald, 2012). The availability of drugs and sex may have a direct impact on HIV transmission, whereas alcohol outlet density may indirectly impact HIV. Higher density of alcohol outlets has been associated with greater alcohol consumption (Scribner, Cohen, & Fisher, 2000; Scribner et al., 2008; Treno, Grube, & Martin, 2003), a powerful determinant of HIV risk behavior. Greater density of alcohol outlets, which may be meeting places for sexual partners, may also lead to segmentation of patrons and sexual networks (Gruenewald, 2007). This network segmentation may lead to changes in network density and other structural network properties that may facilitate or impede HIV transmission (Mukwembi, 2011). Availability may not only influence behaviors through access, it is likely that in areas with increased availability of alcohol, illicit drugs, and sexual exchange, community norms and role models emerge that promote behaviors and descriptive norms regarding the acceptability of HIV-related risk.

Social networks

Another way to conceptualize neighborhoods is based on the social impact of the connections between people who live in neighborhoods. Social network analyses allows for the examination of key individuals that may influence health behaviors. Since HIV transmission is almost always due to a social behavior, social network analyses can examine relationships that lead to HIV transmission and those that may alter transmission dynamics by promoting risk reduction among individuals or altering group level social norms (C. A. Latkin et al., 2009; Wang, Brown, Shen, & Tucker, 2011). Social networks may also provide resources that reduce the need to engage in risk behaviors to acquire resources. Social support from network members may reduce depression and enhance adherence to HIV medications (Knowlton, Curry, Hua, & Wissow, 2009; Knowlton et al., 2011). Network members may also provide resources that increase access to HIV medical care and to voluntary risk reduction counseling and HIV testing (VCT). Networks may also have deleterious influences on sexual and substance use behaviors and mental health (Latkin & Knowlton, 2005).

Social networks and geospatial factors

Neighborhoods and networks are often interlocking. Many network members are located within the same neighborhood and residential propinquity leads to the formation and maintenance of social networks. Several social network perspectives suggest that geographic factors are linked to network disease transmission risks. Core theory hypothesizes that social networks of high transmitters are in geographically bounded areas such that these network configurations perpetuate disease transmissions (Zenilman, Ellish, Fresia, & Glass, 1999). In a study of IDUs and their networks, approximately half of drug and sex network members resided within their neighborhood and only 6% of sexual partners and 3% of drug partners resided more than 5 miles from the participants’ residential location (Tobin, Kuramoto, Davey-Rothwell, & Latkin, 2011). A study by Zenilman and colleagues (1999) found that in core areas the median distance between male gonorrhea patients and their partners was 339 meters, whereas the median distance for those who lived outside of the core was 1,956 meters. Gindi and colleagues (2011b) found that people in areas of high HIV prevalence were more likely to choose sex partners within the same neighborhood. In addition to delineating the difference between core and non-core networks, these findings indicate that in urban areas of the US partners tend to live in the same geographic areas.

One perspective on HIV and geographic area is that of “community level viral load” (Das et al., 2010). Rather than viewing HIV transmission as a result of individual level behaviors, this perspective views a geographic region as a reservoir of HIV and posits that since viral load is a strong predictor of transmissibility of HIV, the community level viral load may predict seroconversion rates within a geographic region. Turnover within social networks may also influence HIV transmission dynamics (De, Cox, Boivin, Platt, & Jolly, 2007; Hu et al., 2002; Morris & Kretzschmar, 1995). High rates of incarceration and reentry within highly impoverished neighborhoods, may also lead to greater turnover within risk networks and hence greater opportunities for HIV to enter certain social networks (Adimora & Schoenbach, 2005).

Diffusion of innovations

Diffusion of innovations, a theory which refers to the process through which new ideas are transmitted within a population (Rogers, 1995), is usually viewed as a social network based approach to behavior change (Li, Weeks, Borgatti, Clair, & Dickson-Gomez, 2012; Weeks et al., 2009). Networks can be within and comprised of organizations and can be geographically based in neighborhoods. Diffusion of behavior change within neighborhoods may be best viewed as diffusion by networks, organizations, and places. Depending on the social organization of neighborhoods it may be best to focus on one, two or three of these interrelated constructs. Utilizing networks to diffuse HIV risk reduction is well-documented as an HIV prevention strategy but it usually has not been conceived of as a geographically based intervention; yet, training a critical number of network members within a geographic area may lead to a critical mass that could lead to sustained behavior change.

Social norms

The behavioral settings literature suggests that certain settings have distinct social norms (Barker, 1968; Brown, Ellard, Mooney-Somers, Hildebrand, & Langdon, 2012; Friedman et al., 2007b; Galea, Ahern, & Vlahov, 2003; Karasek, Ahern, & Galea, 2012). Less is known about norms from a neighborhood perspective. It is likely that certain neighborhood characteristics may cue health behaviors, such as the presence of substance abuse and advertisements for alcohol. Although most network literature has focused on the potential influence of close ties, there is also evidence to suggest the social influence of individuals who are not closely linked (Cialdini, 2005). The social influence of others who are not close may help to explain how individuals within a neighborhood may influence each other’s behaviors (af Hjelmsäter, Granhag, & Stromwall, 2009). Moreover, propinquity often leads to friendships, which may strengthen the influence of neighbors on each other. Social norms have been used in HIV prevention and substance use interventions (Neighbors et al., 2011; Teunissen et al., 2012; Trickett, 2002). An important future area of research is examining how neighborhood factors may mediate, moderate, and maintain social norms and how to structure norm based interventions in neighborhoods.

Policy and policing

Although laws usually do not vary by neighborhoods, the enforcement of laws may vary widely by neighborhood (Cooper, Bossak, Tempalski, Des Jarlais, & Friedman, 2009; Cooper et al., 2012). There is ample evidence that police tactics often interfere with harm reduction activities such as needle exchange (Beletsky, Grau, White, Bowman, & Heimer, 2011; Heimer, Bluthenthal, Singer, & Khoshnood, 1996). Less is known about how policing tactics such as “stop-and-frisk” impedes individuals from carrying HIV prevention materials such as condoms and syringes due to fear that it may be used against them in court cases (Center for Constitutional Rights, July 2012). Moreover, arrest data which is commonly used in measures of neighborhood factors should not be viewed as an accurate reflection of illegal activity because it is also determined by the policing practices in that geographic area.

Zoning

Neighborhood resources extend far beyond social resources. Urban planning and zoning decisions dictate allowable land use within cities, which in turn can shape the resource and service infrastructure within neighborhoods (Ashe, Jernigan, Kline, & Galaz, 2003; Schilling & Linton, 2005; Substance Abuse and Mental Health Services Administration (SAMHSA), 1995). Residential zoning has been designed in most cases to protect the health and well-being of residents and create stability within neighborhoods by clustering compatible land usage and building types. Yet, zoning decisions can have a strong public health impact (Ashe, Jernigan, Kline, & Galaz, 2003; Corburn, 2004). Zoning can dictate the extent to which residents in any one neighborhood are able to walk to a grocery store or pharmacy, how far they need to travel to reach a hospital, how many alcohol or fast food outlets are nearby, how many people can live in a dwelling, residential density, affordable housing options, proximity of industrial and commercial land use, and the extent of lighting and green space in an area. Importantly, these same policies also impact the availability of social services within a neighborhood and can result in over-concentration of services in areas with lower political capital. There are many examples of residential opposition to substance abuse treatment, mental health facilities, needle exchange sites, and halfway houses within neighborhoods (Smith & Hanham, 1981; Substance Abuse and Mental Health Services Administration (SAMHSA), 1995; Takahashi, 1997; Tempalski, Friedman, Keem, Cooper, & Friedman, 2007). These barriers are further compounded by zoning policies that facilitate community resistance by limiting possible locations for such uses to only specific areas (Weber, 2005), often in higher density and more commercial districts. Despite a variety of federal non-discrimination and fair-housing laws, the result is often a geographically segregated service system, with many drug and alcohol treatment facilities, transitional housing programs, and other supportive services located in or near areas of high crime and drug availability. Furthermore, there is a geographic dimension to HIV prevention and care organizations. For example, HIV testing clinics often serve a neighborhood, but some individuals may choose to be tested in a setting that they perceive to be more anonymous. Moreover, if there are few testing centers within a city then it is likely that individuals from different neighborhoods will need to travel to utilize them.

Challenges to studying neighborhood factors and HIV

With hundreds of variables in many geographic databases it is easy to find associations that may be based on chance alone. Moreover, the meaning of these associations is not always apparent. For example, if there’s an association between proportion of female-headed households and sexually transmitted infection (STI) rates, how are we to interpret these associations? Abandoned buildings, per se, do not ‘cause’ HIV acquisition. However, abandoned buildings may be settings where HIV risk behaviors occur, they may be stressors or reduce collective efficacy, or they may be an indicator of neighborhood social economic status. Abandoned buildings may lead to more policing which may lead to less frequent carrying of syringes and consequently more syringe sharing among IDUs. Moreover, although it is unlikely that social drift, with those who are at high risk moving to impoverished neighborhoods, explains the association between neighborhood factors and HIV, it is plausible that individuals who cannot move out of economically disadvantaged neighborhoods may contribute to behaviors and norms that foster HIV transmission.

Correlations among neighborhood factors that make it difficult to delineate causal pathways that lead to HIV-related behaviors, for example, geographic clustering of syringe sharing could be due to localized community norms, concentrated policing, or distance from syringe access points such as syringe exchange locations or pharmacies selling over-the-counter syringes. Cooper and colleagues (2012) found that syringe sharing was less likely in areas with access to syringes and more likely in areas with increased local arrests. Similarly, concentrated overdose mortality has been attributed both to deteriorated neighborhood environments (Hembree et al., 2005) and to higher arrest rates within precincts (Bohnert et al., 2011). Given the complexities of how neighborhood factors may impact HIV behaviors, it is important to not only have geographic data on behaviors and policies but also have information on the history of the neighborhoods to help explain geographically patterned behaviors.

Rural versus urban and suburban neighborhoods

Most studies on HIV risk have focused on urban neighborhood factors. There are pragmatic reasons for focusing on urban areas as neighborhoods may be easier to define within urban areas and usually there are more neighborhoods per geographic area, which allows for more units of analysis. Yet some rural areas have high rates of HIV (Hall, Li, & McKenna, 2005; Reif, Whetten, Ostermann, & Raper, 2006). Relative little is known about the geographic dynamics that facilitate HIV transmission in these areas, and less is known about neighborhood influences on HIV within suburban areas. Some research has investigated the built environment of suburbs, with a strong focus on factors like walkability and proximity of residential and commercial spaces (Frank, Kerr, Rosenberg, & King, 2010; Sturm & Cohen, 2004; Wood et al., 2008). However, the relevance of these and other neighborhood qualities has not been examined in the context of HIV or related behaviors such as drug or alcohol use.

Exposure ‘dose’ in neighborhoods

Most studies of neighborhoods and risk have assessed the association between geographic residential location and health behaviors. Yet not all individuals spend the same amount of time in their neighborhoods (Takahashi, Wiebe, & Rodriguez, 2001). Hence, neighborhoods may have a different impact on the behaviors of those who spend most of their time immersed versus those whose time is primarily spent elsewhere (Leventhal & Dupéré, 2011; Wodtke, Harding, & Elwert, 2011). The amount of time spent in residential neighborhoods may be a function of age and employment status with those who are employed spending less free time in their residential neighborhood. Curry et al. (2008) found that time spent in neighborhoods was associated with depression among drug users, and Frye et al. (2010) reported that that in Florida the level of alcohol consumption was associated with duration of residence among MSM who had moved to the region.

Homelessness and neighborhoods

Homelessness has been consistently found to be a risk factor for HIV acquisition, lack of HIV medical care, and low adherence to HIV medications (Aidala, Cross, Stall, Harre, & Sumartojo, 2005; Aidala, Lee, Abramson, Messeri, & Siegler, 2007; Galea & Vlahov, 2002; Wolitski, Kidder, & Fenton, 2007). Homelessness is sometimes conceptualized as not living in a neighborhood, because homeless individuals may not have a fixed residential address; however, the neighborhood or neighborhoods where they frequent may have a greater impact on their health and well-being as compared to individuals who are housed in the same neighborhood. Homeless individuals may have greater exposure to the conditions on the streets than those housed individuals in the neighborhood. Moreover, the level of homelessness within a neighborhood may be an important factor in HIV transmission due to mixing patterns and risk behaviors. It is also likely that the impact of homelessness differs by neighborhood. For example, residing in a commercial area is likely to be different than staying in a residential area. A potentially important area of research is examining the social geographies of homeless individuals and how it may contribute to risk behaviors.

Segregation

Many neighborhoods are economically and racially segregated. Segregation has been linked to a range of health outcomes (Brondolo, Love, Pencille, Schoenthaler, & Ogedegbe, 2011; White & Borrell, 2011), HIV testing (Ford et al., 2009), and risk networks (Friedman, Cooper, & Osborne, 2009). As racial segregation is often strongly linked to economic segregation, it becomes difficult to disentangle and understand the precise mechanisms underlying neighborhood-related health disparities (Acevedo-Garcia, Lochner, Osypuk, & Subramanian, 2003). One strategy has been to identify and compare proximate neighborhoods with similar socio-economic conditions and racial composition (LaVeist, Pollack, Thorpe Jr., Fesahazion, & Gaskin, 2011). Neighborhoods may also be segregated based on sexual orientation. In cities that have neighborhoods with a large MSM population, these areas may be excellent targets for HIV prevention and care activities but they also may facilitate transmission within the areas due to higher prevalence of HIV as compared to surrounding areas. As neighborhoods are often segregated by social and economic factors it is critical that researchers examine how these factors influence physical and mental health and how to tailor neighborhood interventions based upon these compositional differences.

Neighborhood dynamic factors

Neighborhood research suggests the importance of the social and physical context. Yet often neighborhood factors are modeled as static. Usually, neighborhood level variables, such as census data and police reports are modeled as level two variables along with individual level variables such as HIV risk behaviors. There has been less modeling of how changes in neighborhood factors may influence behaviors -- with the notable exception of the work of Wallace and colleagues (1988) in demonstrating how the closing of firehouses in poor neighborhoods in the Bronx led to greater HIV transmission. Evans-Polce and colleagues (In Press) found that among a sample of drug users and their network members, perceptions of the future potential violence in their neighborhood predicted mental health even after adjusting for current social disorganization. Future studies need to longitudinally examine the influences of neighborhoods as well as how neighborhood level change such as revitalization, urban renewal programs, and rates of foreclosure, may alter HIV prevention and care programs and risk environments. Although researchers may not understand all of the complexities of geographic based pathways that lead to HIV related behaviors, there are many HIV prevention and care interventions that can address neighborhood factors.

Interventions

Interventions to address psychological well being, achievement, and human development have been integrally tied to psychology. Since the beginning of empirical psychology there has been a push for interventions to enhance well-being that goes beyond the individual. Kurt Lewin (1946), in describing the role of research stated, “The second cause of dissatisfaction is the growing realization that mere diagnosis--and surveys are a type of diagnosis---does not suffice. In intergroup relations as in other fields of social management the diagnosis has to be complemented by experimental comparative studies of the effectiveness of various techniques of change” (pg 37).

Community and social psychology

Kurt Lewin’s (1946) emphasis on action research called for research designed to address problems within communities. James Kelly (2007; 2008; 2010) has emphasized an ecological approach to community psychology with developing settings that assist individuals to address developmental and social challenges. Community psychology has also emphasized both the importance of social context, methods of measuring it, and developing interventions that are above the individual level and acknowledge that health behaviors are complex and historically and culturally situated. More recently, community based participatory research (CBPR) has emphasized the role of the community in identifying problems and solutions and developing sustainable approaches to implementing programs and interventions (Berkley-Patton et al., 2010; Corbie-Smith et al., 2011; S. D. Rhodes et al., 2012; M. V. Williams, Palar, & Derose, 2011). CBPR has burgeoned as a field and now has its own journal and conferences.

Settings based interventions

Schools

Schools are critical settings to promote health behaviors within communities, yet given the large number of schools, there have been relatively few school-based HIV prevention interventions, especially condom distribution. It has been documented that provision of condoms in high schools does not increase sexual behaviors, and that rigorous evaluations of school-based sexually transmitted infection (STI) and HIV prevention programs demonstrated significant levels of risk reduction (Basen-Engquist et al., 2001; Kirby & Brown, 1996; Kirby et al., 2004). The dearth of these programs is due in part to political opposition.

Churches

Churches are critical social institutions in many neighborhoods with high rates of HIV. A recent review of church based HIV prevention interventions examined 163 unique citations but found only 11 studies with sufficient details in the US that focused on faith-based institutions and/or congregations (M. V. Williams, Palar, & Derose, 2011). The majority of these studies utilized a community based participatory research (CBPR) approach. Most of these programs partnered with outside organizations such as community based organizations (CBOs) or universities. Although all churches may not support HIV prevention programs for certain populations, given the high number of churches in many urban areas it is likely that some churches will support HIV prevention and care activities. Current studies suggest that churches can be utilized for HIV prevention and care programs (Alder et al., 2007; Francis & Liverpool, 2009; Wingood, Simpson-Robinson, Braxton, & Raiford, 2011). However, greater research is needed to identify structural and organizational factors within churches that lead to effective and sustainable programs. As churches are key organizations in many impoverished neighborhoods, they are also called upon to address a number of health issues as well as social issues and may be overwhelmed by requests to develop HIV prevention and care programs.

Housing projects and other settings

Sikkema and colleagues (2000; 2005) have utilized housing projects as the venue for HIV prevention interventions and others have focused on apartments for seniors who may be at risk for HIV (Schensul, Levy, & Disch, 2003). These settings have the advantage of targeting interventions to geographic areas with high rates of HIV and demarking settings that are of manageable size and may have shared environmental or social dynamics. Although these geographic areas hold promise, understanding the network dynamics for transmission and for social influence may help to target and tailor such interventions. In addition to housing projects, there have been smaller setting based interventions, including bars and beautician shops (Kelly et al., 1991).

Social network interventions

Social network interventions have been successfully utilized for HIV prevention in a variety of settings. One social network approach of training community popular opinion leaders (CPOL) has often focused on risk reduction among gay men, based on the studies of Kelly (Kelly et al., 1991; Kelly et al., 1992; NIMH Collaborative HIV/STD Prevention Trial Group, 2010). Another social network approach has been to train individuals to promote risk reduction within their personal networks. This approach has been successfully utilized with IDUs and heterosexual populations (C. A. Latkin, Mandell, Vlahov, Oziemkowska, & Celentano, 1996; Tobin, Kuramoto, Davey-Rothwell, & Latkin, 2011). Although social networks are often neighborhood based, network interventions seldom directly consider neighborhood factors.

Neighborhood and Community based interventions

Neighborhood approaches to enhance collective efficacy have included the organization of city blocks and training of block leaders for injury prevention (Schwarz, Grisso, Miles, Holmes, & Sutton, 1993), environmental health concerns (Hopper & Nielsen, 1991), and neighborhood-oriented peer outreach models for violence prevention (Webster, Whitehill, Vernick, & Curriero, 2012). These types of interventions have largely not been applied to HIV prevention; yet if many of the social dynamics are similar, such approaches should be considered for neighborhood HIV prevention efforts.

While there have been several well documented successful community-based multimodal prevention interventions for substance abuse, there have been relatively few such approaches in the US for HIV prevention (Biglan, James, LaChance, Zoref, & Joffe, 1988; Fuller et al., 2007; Pentz et al., 1989). Community mobilization has been an effective HIV prevention strategy in a variety of settings primarily outside of the US (Campbell, Nair, & Maimane, 2007; De Jesus, 2007; Rhodes et al., 2012; Trickett, 2002). The lack of community-level interventions in the US may be due in part to the high cost of community-level interventions and issues of how to implement and evaluate community based interventions. Moreover, as the HIV epidemic in the US is not a generalized epidemic except in impoverished urban neighborhoods, community interventions may not be perceived as cost effective or have sufficient political support.

There have been a few large-scale community-based HIV prevention programs in the US. Community based approaches have been used to link drug users to services through pharmacies (Fuller et al., 2007; Rudolph et al., 2010). One community based approach was the CDC five cities AIDS Community Demonstration Projects (Community-level HIV intervention in 5 cities: Final outcome data from the CDC AIDS community demonstration projects.1999; O’Reilly & Higgins, 1991). The NIDA program for HIV prevention targeting IDUs was a combined public health HIV prevention and research project (Stephens, Kwiatkowski, & Booth, 2000). The CDC and NIDA projects highlight the dilemmas of how to adequately implement, evaluate and sustain large scale community based interventions.

Training of psychology students for studying and addressing neighborhoods and HIV

Traditionally, an important domain of training psychology students is in theories and methods of individual-level behavior change. Addressing neighborhood level HIV prevention and care requires training beyond the individual level approach. Adequately training graduate students in psychosocial approaches to neighborhood and community based approaches to HIV prevention and care involves a diverse array of inter-disciplinary skills. In addition to a foundation in community psychology, key skills include GIS and spatial statistics, multilevel modeling, social network analyses, and methods for implementing and evaluating interventions. CBPR contains key elements of such training, with strong emphasis on community engagement and partnership. In addition to training in standard randomized clinical trials (RCT) methodologies, there is also a need for alternatives to RCT methods and assessment techniques, including field ethnography, adaptive designs, and propensity scores. We need to develop settings and field stations that provide opportunities for students and junior faculty to work with and learn about populations at greatest risk for HIV. It is important to acknowledge that addressing neighborhood concentration of HIV-related behaviors requires familiarity with and comfort working within a variety of geographic settings, such as inner-city environments, sex- or drug-markets, and gay-identified neighborhoods. As many institutions of higher education do not have a presence in urban impoverished areas, training programs should consider partnering with existing social and community-based organizations as well as health departments and social service agencies. Moreover, it is critical to train students in cultural competence in working with ethnic and sexual minorities as well as training in the science of substance abuse and in working with people who use drugs.

Conclusions

Neighborhoods are a critical unit of analysis for a wide range of community-based interventions, whether focused directly or indirectly on HIV. Only through ongoing community analyses of social organizations, patterns of interactions, perceived identity, and geographic configuration is it possible to identify the most appropriate geographic and social boundaries for interventions and best strategies for achieving the desired outcomes. For example, changing zoning to reduce the number of alcohol outlets and community approaches to violence prevention are often neighborhood originated, yet may also require sustained advocacy and support from broader constituents. Many social organizations are not neighborhood based or may be linked to several contiguous geographic areas. Schools albeit neighborhood-based are often managed and directed at a district level.

In the mobilization of neighborhoods it is important to ask what are the best organizations to target for neighborhood HIV prevention and care interventions; what organizational analyses are needed to determine this as well as the strengths and needs of the communities; and which organizations can reach at risk individuals, sustain health promotion activities, and introduce and sustain social norms that promote HIV prevention and care? Neighborhoods provide an important heuristic for geographically-based social organization. There are major differences in life experiences and opportunities as well as risks of acquiring HIV based on neighborhoods. These neighborhood level differences are often reflected in social economic status, stressors, drug and alcohol availability, social capital, social norms, collective efficacy, and place identity. Modeling individual behaviors on a geographic level is challenging, as it requires detailed information about community members on a sufficient scale to draw inferences that can be compared across neighborhoods. We need to both develop greater understanding of how neighborhood differences lead to HIV transmission and suboptimal care as well as develop appropriate and sustainable interventions.