Literature DB >> 26599877

Influence of Jail Incarceration and Homelessness Patterns on Engagement in HIV Care and HIV Viral Suppression among New York City Adults Living with HIV/AIDS.

Sungwoo Lim1, Denis Nash2, Laura Hollod3, Tiffany G Harris4,1, Mary Clare Lennon2,5, Lorna E Thorpe2.   

Abstract

OBJECTIVES: Both homelessness and incarceration are associated with housing instability, which in turn can disrupt continuity of HIV medical care. Yet, their impacts have not been systematically assessed among people living with HIV/AIDS (PLWHA).
METHODS: We studied a retrospective cohort of 1,698 New York City PLWHA with both jail incarceration and homelessness during 2001-05 to evaluate whether frequent transitions between jail incarceration and homelessness were associated with a lower likelihood of continuity of HIV care during a subsequent one-year follow-up period. Using matched jail, single-adult homeless shelter, and HIV registry data, we performed sequence analysis to identify trajectories of these events and assessed their influence on engagement in HIV care and HIV viral suppression via marginal structural modeling.
RESULTS: Sequence analysis identified four trajectories; 72% of the cohort had sporadic experiences of both brief incarceration and homelessness, whereas others experienced more consistent incarceration or homelessness during early or late months. Trajectories were not associated with differential engagement in HIV care during follow-up. However, compared with PLWHA experiencing early bouts of homelessness and later minimal incarceration/homelessness events, we observed a lower prevalence of viral suppression among PLWHA with two other trajectories: those with sporadic, brief occurrences of incarceration/homelessness (0.67, 95% CI = 0.50,0.90) and those with extensive incarceration experiences (0.62, 95% CI = 0.43,0.88).
CONCLUSIONS: Housing instability due to frequent jail incarceration and homelessness or extensive incarceration may exert negative influences on viral suppression. Policies and services that support housing stability should be strengthened among incarcerated and sheltered PLWHA to reduce risk of adverse health conditions.

Entities:  

Mesh:

Year:  2015        PMID: 26599877      PMCID: PMC4657891          DOI: 10.1371/journal.pone.0141912

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


Introduction

Maintaining continuous engagement in HIV medical care is critical for HIV disease management for people living with HIV/AIDS (PLWHA) [1, 2]. Housing stability is considered to be an important determinant of retention in HIV medical care and for achieving and sustaining viral suppression because it helps enable PLWHA to attend regular medical visits and adhere to antiretroviral medications [3]. Housing stability may also provide other less quantifiable benefits such as stronger social networks and a sense of identity, which some researchers have postulated may motivate individuals to avoid risk behaviors and to maintain health [3]. Empirical evidence to support this relationship has been documented among PLWHA with histories of homelessness. For example, according to longitudinal data from a representative sample of New York City (NYC) PLWHA, self-reported receipt of assistance for housing problems was positively associated with appropriate HIV medical care [4]. Similarly, several studies have reported higher likelihoods of adherence to antiretroviral treatment among stably-housed PLWHA versus their homeless or unstably housed counterparts [5-7]. Along with homelessness, incarceration disrupts individuals’ housing stability and contributes to housing instability after release from incarceration. However, the association between housing stability and HIV care has rarely been described among formerly incarcerated PLWHA; current evidence is mainly concentrated on disrupted HIV care post release [8-10]. Because both events affect housing stability and incarceration is strongly correlated with homelessness, it is important to take into account dynamic aspects of incarceration events along with homelessness to more accurately characterize the impact of housing instability on continuity of HIV care. The purpose of this paper was to examine whether and how different patterns of jail incarceration and homelessness influence continuity of HIV care and HIV viral suppression among NYC PLWHA with recent experiences of both jail incarceration and homelessness, using a measure that captures sequencing and duration of jail incarceration and homelessness. Specifically, the study tested the hypothesis that frequent transitions between jail incarceration and homelessness are associated with lower likelihood of subsequent engagement in HIV care and viral suppression, plausibly due to the greater housing instability of PLWHA with this pattern.

Materials and Methods

Data source

The study population included 1,698 NYC adults who, prior to 2005, were diagnosed with HIV/AIDS, alive, and had spent at least one night in both NYC jail and NYC single adult homeless shelters during 2001–05. To understand dynamics between jail incarceration and homelessness, we focused on those with both types of events. They represented about 2% of NYC PLWHA during this same period. The main data source came from the combined administrative data from NYC jail and NYC single adult shelter registries, which provided jail incarceration/shelter use records and baseline demographic and criminal information. These data were then matched with the population-based NYC Department of Health and Mental Hygiene HIV/AIDS surveillance registry that contains demographic and clinical information on all diagnoses of HIV and AIDS reported in NYC, with the addition of comprehensive HIV-related laboratory reporting (including CD4 counts and viral loads test results) and deaths. This probabilistic matching process was evaluated and validation results have been published [11]. We used June 2005-June 2006 as the follow-up period for evaluating outcomes (described below) and utilized HIV laboratory test results from this time because complete viral load and CD4 test results were captured only after the New York State mandatory reporting law became effective as of June 1, 2005 [12]. Thus, to be eligible for this analysis, a PLWHA had to be alive as of January 1, 2005, which allowed us to examine HIV care outcomes during the one year follow-up time. While censoring those who died before 2005 could potentially introduce bias, this was unlikely as baseline demographic and clinical characteristics were similar between those who died during 2001–04 (n = 45) and those who survived (n = 1,698; data not shown). A small number of deaths were identified during the one year follow-up timeframe and were censored accordingly in the calculation of person-years. For deaths in 2005, 0.5 person-year was assigned (n = 64). The comparison group was comprised of NYC PLWHA who were neither incarcerated nor sheltered in a single adult shelter during 2001–05 according to an administrative database match, and were alive as of January 1, 2005 according to the NYC HIV/AIDS surveillance registry. Similar to the study population, June 2005-June 2006 was used as the follow-up period for the comparison group. The NYC Department of Health and Mental Hygiene Institutional Review Board determined that this study was not subject to institutional board review because it is not human subject research.

Variables

Two primary outcome variables were examined in this analysis: (1) continuity of HIV medical care and (2) HIV viral suppression [2]. Continuity of HIV medical care was defined as having at least two viral load or CD4 tests during June 2005-June 2006, which were ≥90 days apart [1]. Viral suppression was defined as being achieved if there was at least one record with a viral load of <400 copies/ml during the 12-month period [2]. The exposure variable was defined using group-based trajectories of jail incarceration/homelessness during 2001–05. Analytic approaches and results of sequence analysis performed to determine these group based trajectories have been published elsewhere [13]. Potential confounders for exposure-outcome association were identified by constructing a specific Directed Acyclic Graph for this analysis [14]. These included baseline demographic characteristics (age, sex, race/ethnicity, poverty levels of neighborhoods of residency at the time of incarceration), a proxy for substance use (i.e., being charged with drug possession or transferred to substance use treatment clinics), a proxy for serious mental illness (i.e., transferred to state psychiatric hospitals or mental health treatment clinics), type of criminal charges (drug sales, violent crimes, weapon possession, public administration, property crimes, quality of life crimes, and sex crimes), age at HIV diagnosis, and development of AIDS (AIDS defining opportunistic illness or CD4 nadir of 200 cells/uL or less) [13].

Statistical analysis

First, descriptive statistics of baseline characteristics and HIV care outcomes were summarized across trajectory groups of jail incarceration and homelessness. Bivariate association between each of these characteristics and trajectory groups was evaluated using chi-square test for categorical variables or independent t-test with Bonferroni adjustment for continuous variables. Then, marginal structural log-linear Poisson regression analysis with an offset of person-years was performed to estimate adjusted relationships between trajectories of jail incarceration/homelessness and HIV care outcomes. A stabilized inverse probability of treatment weight (IPTW) was derived from a propensity score model using trajectory groups (dependent variable) and baseline demographic, behavioral, and criminal characteristics (independent variables). Estimates from marginal structural modeling were weighted using IPTW to balance baseline characteristics across trajectory groups to improve exchangeability, ensure positivity (tightly distributed IPTW with one as a mean value), and meet stable unit treatment value assumptions (adjusting for poverty levels of neighborhood residency to address potential data dependency among some study subjects) [15-17]. A sandwich estimator for variance and a corresponding p-value were calculated because it was robust against model misspecification [16]. Multiple imputations via IVEware software were performed to address missing data (sex: 1% missing, race/ethnicity: 1% missing, nativity: 1% missing, poverty levels of neighborhood residency at the time of incarceration: 25% missing), which generated five imputed datasets [18]. A subset of PLWHA was then re-created and combined results of five estimates were reported according to Schafer’s approach, which accounts for within- and between-imputation variability [19]. Because the study did not collect information about behavioral and all clinical characteristics associated with retention in HIV care or viral suppression (e.g., injecting drug use), causal estimates from marginal structural modeling were potentially biased due to unobserved confounding. In a sensitivity analysis, we assessed the extent to which causal estimates might be influenced by bias due to unobserved confounding by employing VanderWeele and Arah’s bias formula derived from the relationship between outcome and unobserved confounder and that between exposure and unobserved confounder [20]. All analyses except for sequence analysis (R 2.14.2, Vienna, Austria) and imputation (IVEware) were performed using SAS 9.2 software (Cary, NC). Statistical significance was established if two sided p-value <0.05.

Results

A total of 1,698 individuals living with HIV/AIDS had at least one jail incarceration event in a NYC jail and spent at least one night at a NYC single adult shelter during January 2001–May 2005. Compared with NYC PLWHA who did not experience jail incarceration or homelessness during the study period (N = 84,659), this study population was disproportionately male (84% vs. 69%) and non-Hispanic black (65% vs. 45%), and the percent of non-Hispanic whites (4% vs. 21%) and residents living in medium poverty neighborhoods (14% vs. 29%) was much smaller (Table 1). In contrast, the age distribution and stage of HIV infection were similar between the two groups.
Table 1

Demographic and criminal characteristics by five trajectory groups among 1,698 adults living with HIV/AIDS who were incarcerated in New York City jail and spent at least one night at New York City single adult shelter in January 2001–May 2005.

 NYC PLWHA a TotalTemporaryContinuous incarcerationContinuous shelter useDecreasing shelter use
Total84,6591,69812303176190
Exposure in 1/2001–5/2005
Average # of incarceration events33623
Average days in jail139873697185
Average jail days per incarceration49371053929
Average # of shelter use events6563412
Average days in shelters925352728327
Average shelter days per shelter event141195356
Age as of 6/2002 b
    18–24 years4%6%6%5%8%7%
    25–34 years17%24%24%27%13%20%
    35–44 years39%50%49%53%44%53%
    45–54 years30%18%18%15%28%19%
    55–89 years10%2%3%1%7%1%
Sex c
    Male69%83%83%84%84%82%
    Female31%17%17%16%16%17%
Race/ethnicity c
    Non-Hispanic white23%5%5%3%5%2%
    Non-Hispanic black43%64%62%68%62%81%
    Hispanic32%30%32%27%30%17%
    Asian1%0%0%0%0%0%
    Others/unknown1%1%1%1%3%0%
Nativity c
    United States born62%93%92%94%90%96%
    Foreign born13%7%8%6%10%4%
Poverty levels of neighborhood of residency
    Low (<10% below poverty)5%2%2%3%3%2%
    Medium (10 to <20%)31%15%15%16%18%12%
    High (20 to <30%)15%9%9%10%5%8%
    Very high (≥30%)38%43%43%44%38%40%
    Missing11%31%31%27%36%38%
Types of criminal charges
    Drug possession43%40%59%34%39%
    Drug sales26%23%36%33%22%
    Violence27%24%38%26%28%
    Public administration30%28%39%28%34%
    Property43%37%63%38%43%
    Weapons3%3%4%3%0%
    Quality of life7%7%8%7%7%
    Sex crimes2%2%2%7%4%
Substance use d 46%41%60%48%48%
Serious mental illness d 2%2%3%2%6%
Age at HIV diagnosis
    13–24 years10%10%10%9%8%8%
    25–49 years79%84%83%87%77%86%
    50+ years11%6%7%4%15%7%
Stage of HIV infection at diagnosis e
    Early (HIV only)95%96%96%97%95%96%
    Late (HIV/AIDS)5%4%4%3%5%4%

aNon-incarcerated/non-sheltered NYC residents living with HIV/AIDS.

bBecause age was calculated at the end of year according to NYC HIV registry and raw birthdate information was not available, age of non-incarcerated/non-sheltered PLWHA was as of 12/31/2002.

cBecause of a small % of missing data (sex: 1%, race/ethnicity: 1%, nativity: 1%) in the study cohort, sum of these numbers were not matched up with total numbers of individuals. For non-incarcerated/non-sheltered PLWHA, % of missing data were much greater than that among the study cohort.

dProxy measures were used to capture substance use and prior severe mental illness conditions.

eStage of HIV infection was determined according to the concurrent diagnosis where there is an AIDS diagnosis within 31 days of an HIV diagnosis.

aNon-incarcerated/non-sheltered NYC residents living with HIV/AIDS. bBecause age was calculated at the end of year according to NYC HIV registry and raw birthdate information was not available, age of non-incarcerated/non-sheltered PLWHA was as of 12/31/2002. cBecause of a small % of missing data (sex: 1%, race/ethnicity: 1%, nativity: 1%) in the study cohort, sum of these numbers were not matched up with total numbers of individuals. For non-incarcerated/non-sheltered PLWHA, % of missing data were much greater than that among the study cohort. dProxy measures were used to capture substance use and prior severe mental illness conditions. eStage of HIV infection was determined according to the concurrent diagnosis where there is an AIDS diagnosis within 31 days of an HIV diagnosis. Fig 1 shows that among the 1,698 PLWHA experiencing both jail incarceration and homelessness from January 2001–May 2005, events were best represented by four unique trajectories. The majority (72%) had brief, intermittent jail incarceration and shelter stays during that time (n = 1,230; hereinafter Temporary). The second most common trajectory pattern (19%) included adults who spent extensive amounts of uninterrupted time in jail from January 2001–May 2005 (Continuous incarceration; n = 317). About 9% of the study cohort exhibited one of two trajectories characterized by unique shelter use patterns; one group spent extensive amounts of time in shelters (average 728 days) without much interruption, classified as having a continuous shelter use pattern (n = 61), and the other had continuous shelter stays during earlier months followed by periods with sporadic occurrences of brief jail incarceration/shelter stays (Decreasing shelter use; n = 90).
Fig 1

Four non-overlapping groups of jail incarceration/homelessness trajectories according to sequence analysis among 1,698 adults living with HIV/AIDS who spent at least one night in a New York City jail and at least one night at a New York City single adult homeless shelters in January 2001–May 2005.

This figure describes trajectories of jail incarceration and homelessness in January 2001–May 2005. 4 trajectory groups represent distinct trajectories that were identified by sequence analysis and each individual belongs to one of 4 groups. Legend: Yellow color: Community-dwelling; Blue color: incarceration; Red color: homelessness

Four non-overlapping groups of jail incarceration/homelessness trajectories according to sequence analysis among 1,698 adults living with HIV/AIDS who spent at least one night in a New York City jail and at least one night at a New York City single adult homeless shelters in January 2001–May 2005.

This figure describes trajectories of jail incarceration and homelessness in January 2001–May 2005. 4 trajectory groups represent distinct trajectories that were identified by sequence analysis and each individual belongs to one of 4 groups. Legend: Yellow color: Community-dwelling; Blue color: incarceration; Red color: homelessness Individuals with Continuous shelter use pattern were older than those in other groups (Table 1). Race/ethnicity, sex, nativity, and neighborhood poverty were unrelated to trajectory group. Across all trajectory groups, approximately half of the study cohort had an indication of substance use, while prevalence of serious mental illness was highest in the Decreasing shelter use group. Individuals charged with drug possession, drug sales, property, and violent crimes were more likely to exhibit the Continuous incarceration trajectory compared to those with other criminal charges. Age at HIV diagnoses and likelihood of progression to AIDS were similar across trajectory groups. Among the study cohort, 50% had at least two HIV-related laboratory tests for viral load or CD4 count, which were ≥90 days apart during one-year follow-up time (Table 2). This was similar among non-incarcerated/non-sheltered NYC PLWHA, 50% of whom also experienced at least two HIV lab tests in the same period. Prevalence of engagement in HIV care was roughly similar across all trajectory groups, ranging from 41% to 53%. During June 2005-June 2006, 29% of the study cohort experienced viral suppression; prevalence of viral suppression was highest among individuals who stayed in shelters during the early months and dwelled in the community afterwards (Decreasing shelter use). During the same period, 41% of non-incarcerated/non-sheltered NYC PLWHA experienced viral suppression.
Table 2

Percentages of continuity of HIV care and HIV viral suppression by trajectory groups among adults living with HIV/AIDS with recent experiences of jai incarceration and homelessness, New York City, June 2005-June 2006.

N% of continuity of HIV care a % of viral suppression a
Non-incarcerated/non-sheltered NYC PLWHA84,659 b 51%41%
The study population1,69850%29%
Temporary123053%29%
Continuous incarceration31741%26%
Continuous shelter use6148%31%
Decreasing shelter use9049%41%

aContinuity of HIV care was defined as having at least two viral load or CD4 tests during June 2005-June 2006, which were ≥90 days apart. Viral suppression was defined as being achieved if there was at least one record with a viral load of <400 copies/ml during the 12-month period.

bNon-incarcerated/non-sheltered NYC PLWHA who were diagnosed and alive before 2005.

aContinuity of HIV care was defined as having at least two viral load or CD4 tests during June 2005-June 2006, which were ≥90 days apart. Viral suppression was defined as being achieved if there was at least one record with a viral load of <400 copies/ml during the 12-month period. bNon-incarcerated/non-sheltered NYC PLWHA who were diagnosed and alive before 2005. Results from marginal structural regression analysis showed that trajectories of jail incarceration and homelessness were not significantly associated with subsequent engagement in HIV care during June 2005-June 2006 (Table 3). Among NYC PLWHA with recent histories of jail incarceration and homelessness, those with Temporary relative to Decreasing shelter use patterns had 0.67 times lower prevalence of viral suppression during the same one-year period (95% Confidence Interval (CI) = 0.50, 0.90). In addition, those with Continuous incarceration pattern were less likely to experience viral suppression, compared with those with Decreasing shelter use pattern (PR = 0.62, 95% CI = 0.43, 0.88).
Table 3

Prevalence ratio for continuity of HIV care and HIV viral suppression by trajectory groups among 1,698 adults living with HIV/AIDS with recent experiences of jai incarceration and homelessness, New York City, June 2005-June 2006.

Trajectory groupsContinuity of HIV careHIV viral suppression
PR a , b 95% CI b PR a , b 95% CI b
Temporary1.040.82, 1.32 0.67 0.50, 0.90
Continuous incarceration0.810.61, 1.07 0.62 0.43, 0.88
Continuous shelter use0.760.49, 1.170.710.52, 1.22
Decreasing shelter useReferenceReference

CI, confidence interval; PR, prevalence ratio.

Prevalence ratio was estimated from log-linear Poisson models. Numbers in bold indicate statistical significance at p <0.05.

bInverse probability of treatment weight was used to control for bias due to confounding. Covariates for the model for continuity of HIV care included age, sex, race/ethnicity, nativity, neighborhood poverty, a proxy measure of substance use, a proxy measure of mental illness, criminal charges due to drug sales, violent crimes, weapon possession, public administration, property crimes, quality of life crimes, sex crimes, ages of HIV diagnoses, and stage of HIV infection. The same sets of covariates except for criminal charges due to weapon possession were used for the model for viral suppression.

CI, confidence interval; PR, prevalence ratio. Prevalence ratio was estimated from log-linear Poisson models. Numbers in bold indicate statistical significance at p <0.05. bInverse probability of treatment weight was used to control for bias due to confounding. Covariates for the model for continuity of HIV care included age, sex, race/ethnicity, nativity, neighborhood poverty, a proxy measure of substance use, a proxy measure of mental illness, criminal charges due to drug sales, violent crimes, weapon possession, public administration, property crimes, quality of life crimes, sex crimes, ages of HIV diagnoses, and stage of HIV infection. The same sets of covariates except for criminal charges due to weapon possession were used for the model for viral suppression. Results from the sensitivity analysis showed how the upper bound of 95% CI for the prevalence ratio for viral suppression could be affected by adjusting for unobserved confounding (see S1 Fig). As long as the association between unobserved behaviors and viral suppression was greater than 1 and particular behaviors (e.g., injecting drug use) among individuals with Temporary relative to Decreasing shelter use patterns were more prevalent (δ >1), the estimated prevalence ratio would have remained significant. On the other hand, if particular behaviors among individuals with Temporary relative to Decreasing shelter use patterns were 20% less prevalent (δ = 0.8) and association between these unobserved behaviors and viral suppression was strong (PR ≥ 2.5 or γ ≥ 2.5), the estimated prevalence ratio would not have been statistically significant.

Discussion

In this study, almost half of NYC adults living with HIV/AIDS who were sheltered and incarcerated from January 2001–May 2005 experienced inadequate engagement in HIV care during the one-year follow-up period. This percentage was similar between the study cohort and non-incarcerated/non-sheltered NYC PLWHA who were diagnosed and alive prior to 2005. Unlike with measures of HIV care engagement, however, overall prevalence of viral suppression was much lower among the study cohort relative to non-incarcerated/non-sheltered NYC PLWHA, suggesting that treatment initiation and/or adherence to treatment might be more difficult among PLWHA with exposure to jail incarceration and homelessness. Within this population of NYC PLWHA who experienced jail incarceration and homelessness, those who sporadically experienced such events or spent extensive amounts of time in jail from January 2001–May 2005 were less likely to experience viral suppression during the one-year follow-up period compared with those who left homeless shelters during early months and rarely returned. However, there was no difference in engagement in HIV care by trajectory group. The null association between trajectories of jail incarceration/homelessness and engagement in HIV care did not support the hypothesis that frequent transitions of short-term jail incarceration and homelessness are associated with poor engagement in HIV primary care. Prevalence of HIV care engagement (51%), regardless of trajectory group, was similar to that among non-incarcerated/non-sheltered NYC PLWHA (50%). It was higher than that among youth and adults living with HIV/AIDS in 13 United States jurisdictions (45%) [1], and than what was observed for formerly-incarcerated PLWHA in 10 United States urban areas who were followed for 6 months after release from jail (38%) [21]. Our finding implies that those with recent histories of incarceration and homeless events were able to receive regular HIV care. Since affordable HIV medical services and various social services are widely available in NYC via safety net programs such as the Ryan White program, and are promoted in NYC neighborhoods, jails, and homeless shelters, experiencing life disruptions due to jail incarceration and homelessness might not act as a barrier to subsequent continuity of HIV care for those already connected to care [12]. Unlike engagement in care, prevalence of viral suppression significantly differed by trajectories of jail incarceration and homelessness. This implies that initiation of and/or adherence to treatment might be more difficult among PLWHA with sporadic, often frequent, exposure to brief jail incarceration and homelessness or those with extensive incarceration experiences, compared with those who had shelter stays only during the early portion of the study period with rare return to shelters or incarcerations subsequently. Given that permanent housing assistance and services were available to NYC PLWHA who qualified, this finding may reflect better access to services such as case management among the reference group that resulted in their being started on treatment and/or assisted them in adhering to HIV treatment regimens. Another possible mechanism is that being persistently out of shelter and jail is indicative of housing stability. Housing stability and the associated likelihood of medication adherence may influence some provider decisions about whether or not initiate HIV treatment [3]. Adults experiencing the Continuous incarceration pattern, as opposed to Decreasing shelter use pattern, were also less likely to achieve viral suppression, whereas there was no significant difference between those with Continuous shelter use pattern and the reference group. This difference between the two continuous patterns may suggest that incarcerated NYC PLWHA experience more difficulty being connected to housing services and experiencing housing stability compared with those in shelters during the early 2000s, which could negatively impact initiation of and/or adherence to HIV treatment regimens [22]. Additionally, because those with continuous incarceration experiences were more likely to be transferred from jails to prisons and clinical data from prisons were missing, viral suppression status could have been misclassified (and the proportion virally suppressed underestimated). This limitation, along with post-release challenges of stable housing, might partly explain why low viral suppression was observed among those with extensive jail incarceration, unlike previous studies that reported positive impacts of incarceration on viral suppression during incarceration [23,24]. Additional data on housing, case services, and prison data are needed to fully understand the mechanism that particular trajectories were associated with viral suppression, while engagement in HIV care was independent of trajectories of incarceration/homelessness. The study finding supports our conclusion from previous work that excess risk of HIV-related mortality associated with the Temporary pattern could be a manifestation of disruptions to HIV treatment due to transitions between jails and shelters [13]. In the current study, viral suppression may act as a mediator of the Temporary pattern-HIV-related mortality association. Sporadic experiences of brief jail incarceration and homelessness, as opposed to undisrupted community-dwelling, may contribute to elevating HIV-related mortality risk among NYC PLWHA with recent incarceration and homelessness by creating environments where essential HIV care and adherence cannot be initiated and/or gets disrupted. Future studies that link mortality data with data form jail and shelter registries and the HIV surveillance registry are warranted to further explore and test mechanisms, such as declining CD4 counts, which may contribute to excess HIV-related mortality associated with a pattern of sporadic exposure to brief jail incarceration and homelessness. This study has some limitations. First, there were limited data on demographic, behavioral, and clinical characteristics of PLWHA who were both incarcerated and sheltered. Despite use of proxy measures of mental illness and substance use, we might not have been able to completely capture PLWHA with these conditions. Individuals with Temporary pattern may be different in systematic ways that may be causally related to risk for not initiating HIV treatment and/or HIV treatment non-adherence than those with Decreasing shelter use pattern. Depending on the direction of unobserved confounding between these patterns, the relationship between viral suppression and Temporary pattern could be biased either toward or away from the null, as seen in the sensitivity analysis. For example, suppose that 50% of individuals with Temporary pattern had no documented history of injecting drug use. If the percent of non-injecting drug users among Decreasing shelter use individuals was 63% and non-injecting drug users were 2.5 times or higher more likely to experience viral suppression, Temporary versus Decreasing shelter use pattern would have been no longer significantly associated with viral suppression. Second, data about housing quality and types of housing services were not collected. Even though homeless PLWHA in NYC have a legal right to be housed, being out of shelter and jail does not necessarily mean being stably housed in the community, and some types of housing assistance are more likely to facilitate stability than others. Third, we considered PLWHA who did not have viral load test results during the analytic period to be virally unsuppressed [25]. Because test results from state prisons could not be included in this analysis and PLWHA with Continuous incarceration pattern were more likely to move to state prisons than those with other patterns, selection bias could not be ruled out. Fourth, data about antiretroviral treatment were not available for analyses. Without knowing length of time under the treatment, understanding an impact of housing stability on viral suppression was limited. Lastly, because antiretroviral treatment was not recommended for all PLWHA and recommendations were only tied to low CD4 count rather than high viral loads during the study period, lack of viral suppression might not serve as a proxy for lack of care of poor adherence. Although stage of HIV infection at diagnosis was controlled for, drawing a linkage between viral suppression and HIV treatment should be made with caution. Despite these limitations, a main strength of the study is the use of a measure that captured dynamic aspects of jail incarceration and homelessness, potentially reflecting differing levels of housing instability over time. In addition, use of IPTW allowed for explicitly testing causal assumptions, further strengthening internal validity of the finding. Lastly, administrative data provided almost complete coverage of HIV-related outcome ascertainment among PLWHA in NYC. In conclusion, this study suggests that life disruption due to jail incarceration and homelessness does not appear to introduce additional barriers to receiving HIV care at recommended intervals but may exert negative influences on achieving and maintaining viral suppression, which is associated with poor clinical outcomes, survival, and onward HIV transmission. It also highlights the relatively better outcomes among the reference group (i.e., higher prevalence of viral suppression) who might experience stable community-dwelling for a longer period. This finding provides important evidence for policies and services (e.g., case management) in support of housing stability among incarcerated and sheltered PLWHA in order to reduce risk of adverse health conditions.

Estimated upper bound of 95% confidence interval of prevalence ratio for HIV viral suppression by the Temporary pattern adjusted for an unobserved confounder (U) among 1,698 PLWHA with jail incarceration and homelessness, New York City, June 2005-June 2006.

This figure illustrates the results from the sensitivity analysis. Lines represent varying estimates of upper bound of 95% confidence interval of prevalence ratio for HIV viral suppression by Temporary pattern over Decreasing shelter use pattern, depending on varying prevalence estimates of unobserved confounder and association between HIV viral suppression and unobserved confounder. (DOCX) Click here for additional data file.
  22 in total

1.  Medicine and the epidemic of incarceration in the United States.

Authors:  Josiah D Rich; Sarah E Wakeman; Samuel L Dickman
Journal:  N Engl J Med       Date:  2011-06-02       Impact factor: 91.245

2.  Monitoring outcomes for newly diagnosed and prevalent HIV cases using a care continuum created with New York city surveillance data.

Authors:  Ellen W Wiewel; Sarah L Braunstein; Qiang Xia; Colin W Shepard; Lucia V Torian
Journal:  J Acquir Immune Defic Syndr       Date:  2015-02-01       Impact factor: 3.731

3.  Optimization of human immunodeficiency virus treatment during incarceration: viral suppression at the prison gate.

Authors:  Jaimie P Meyer; Javier Cepeda; Johnny Wu; Robert L Trestman; Frederick L Altice; Sandra A Springer
Journal:  JAMA Intern Med       Date:  2014-05       Impact factor: 21.873

4.  All-cause, drug-related, and HIV-related mortality risk by trajectories of jail incarceration and homelessness among adults in New York City.

Authors:  Sungwoo Lim; Tiffany G Harris; Denis Nash; Mary Clare Lennon; Lorna E Thorpe
Journal:  Am J Epidemiol       Date:  2015-02-05       Impact factor: 4.897

5.  Retention in care of adults and adolescents living with HIV in 13 U.S. areas.

Authors:  H Irene Hall; Kristen Mahle Gray; Tian Tang; Jianmin Li; Luke Shouse; Jonathan Mermin
Journal:  J Acquir Immune Defic Syndr       Date:  2012-05-01       Impact factor: 3.731

6.  Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders.

Authors:  Tyler J Vanderweele; Onyebuchi A Arah
Journal:  Epidemiology       Date:  2011-01       Impact factor: 4.822

7.  Correlates of retention in HIV care after release from jail: results from a multi-site study.

Authors:  Amy L Althoff; Alexei Zelenev; Jaimie P Meyer; Jeannia Fu; Shan-Estelle Brown; Panagiotis Vagenas; Ann K Avery; Jacqueline Cruzado-Quiñones; Anne C Spaulding; Frederick L Altice
Journal:  AIDS Behav       Date:  2013-10

8.  Vital signs: HIV prevention through care and treatment--United States.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2011-12-02       Impact factor: 17.586

9.  HIV in people reincarcerated in Connecticut prisons and jails: an observational cohort study.

Authors:  Jaimie P Meyer; Javier Cepeda; Sandra A Springer; Johnny Wu; Robert L Trestman; Frederick L Altice
Journal:  Lancet HIV       Date:  2014-11-01       Impact factor: 12.767

10.  Constructing inverse probability weights for marginal structural models.

Authors:  Stephen R Cole; Miguel A Hernán
Journal:  Am J Epidemiol       Date:  2008-08-05       Impact factor: 4.897

View more
  16 in total

1.  The Missing Link: HIV, Corrections, and Public Health.

Authors:  Anne C Spaulding
Journal:  Am J Public Health       Date:  2017-05       Impact factor: 9.308

2.  Exploring the Healthcare Environment and Associations with Clinical Outcomes of People Living with HIV/AIDS.

Authors:  Mary Hawk; Robert W S Coulter; James E Egan; Mackey Reuel Friedman; Steven Meanley; Stuart Fisk; Courtney Watson; Suzanne Kinsky
Journal:  AIDS Patient Care STDS       Date:  2017-11-17       Impact factor: 5.078

3.  Health Literacy Among a Formerly Incarcerated Population Using Data from the Transitions Clinic Network.

Authors:  Kristie B Hadden; Lisa Puglisi; Latrina Prince; Jenerius A Aminawung; Shira Shavit; David Pflaum; Joe Calderon; Emily A Wang; Nickolas Zaller
Journal:  J Urban Health       Date:  2018-08       Impact factor: 3.671

4.  Impact of a New York City Supportive Housing Program on Housing Stability and Preventable Health Care among Homeless Families.

Authors:  Sungwoo Lim; Tejinder P Singh; Gerod Hall; Sarah Walters; L Hannah Gould
Journal:  Health Serv Res       Date:  2018-03-12       Impact factor: 3.402

5.  The Influence of Housing Status on the HIV Continuum of Care: Results From a Multisite Study of Patient Navigation Models to Build a Medical Home for People Living With HIV Experiencing Homelessness.

Authors:  Serena Rajabiun; Janell Tryon; Matt Feaster; Amy Pan; Lisa McKeithan; Karen Fortu; Howard J Cabral; Deborah Borne; Frederick L Altice
Journal:  Am J Public Health       Date:  2018-12       Impact factor: 9.308

6.  Prioritizing homelessness in emergency medicine education: A concept paper.

Authors:  Benedict C Del Buono; Bisan A Salhi; Alexis E Kimmel; Sally A Santen; Kelli L Jarrell; Melissa H White; Christopher K Brown; Joel L Moll
Journal:  AEM Educ Train       Date:  2022-06-23

7.  Exploring Lifetime Accumulation of Criminal Justice Involvement and Associated Health and Social Outcomes in a Community-Based Sample of Women who Use Drugs.

Authors:  Jennifer Lorvick; Megan Comfort; Alex H Kral; Barrot H Lambdin
Journal:  J Urban Health       Date:  2018-08       Impact factor: 3.671

8.  One Size Fits (n)One: The Influence of Sex, Age, and Sexual Human Immunodeficiency Virus (HIV) Acquisition Risk on Racial/Ethnic Disparities in the HIV Care Continuum in the United States.

Authors:  Fidel A Desir; Catherine R Lesko; Richard D Moore; Michael A Horberg; Cherise Wong; Heidi M Crane; Michael Silverberg; Jennifer E Thorne; Beth Rachlis; Charles Rabkin; Angel M Mayor; William C Mathews; Keri N Althoff
Journal:  Clin Infect Dis       Date:  2019-02-15       Impact factor: 9.079

9.  Young Transgender Women of Color: Homelessness, Poverty, Childhood Sexual Abuse and Implications for HIV Care.

Authors:  Elizabeth A Eastwood; Amanda J Nace; Sabina Hirshfield; Jeffrey M Birnbaum
Journal:  AIDS Behav       Date:  2021-07

10.  Housing Subsidies and Housing Stability are Associated with Better HIV Medical Outcomes Among Persons Who Experienced Homelessness and Live with HIV and Mental Illness or Substance Use Disorder.

Authors:  Ellen W Wiewel; Tejinder P Singh; Yaoyu Zhong; Christopher M Beattie; Sungwoo Lim; Sarah Walters; Sarah L Braunstein; John Rojas
Journal:  AIDS Behav       Date:  2020-11
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.