Risk Factors for Human Papillomavirus-Associated Cancers Among People Living with HIV in Washington, District of Columbia.

District of Columbia (DC) has high rates of HIV infection and human papillomavirus (HPV)-associated cancers. People living with HIV (PLWH) are at risk for developing HPV-associated cancers. Previous studies identified factors that may further increase the risk of HPV-associated cancer among PLWH such as age, race/ethnicity, sex, risk factor for HIV transmission, stage of HIV infection, and age at HIV diagnosis. The extent to which PLWH in DC are affected by HPV-associated cancers has not previously been well described, and to our knowledge, the relationship between bacterial sexually transmitted infections (STIs) and subsequent development of HPV-associated cancer among PLWH in DC has not been explored. This was a retrospective case-control analysis of surveillance data on cancer, STIs, and HIV in Washington, DC from 1996 to 2015. There were 20,744 PLWH included in this study, of whom 335 (1.6%) had been diagnosed with an HPV-associated cancer. Among males living with HIV (MLWH), for every additional STI per 10 person-years, risk of developing an HPV-associated cancer increased by 11%. Exposure to STIs was not a significant risk factor for HPV-associated cancer among females. Ever being diagnosed with stage three HIV infection increased risk of HPV-associated cancers among males by 109% and females living with HIV by 111%. STI exposures were associated with HPV-associated cancers among MLWH in DC and ever being diagnosed with advanced HIV infection was associated with HPV-associated cancers among all PLWH. Clinicians treating MLWH should ensure their patients receive primary HPV infection prevention and HPV-associated cancer screenings.

Ending the HIV epidemic using National HIV Behavioral Surveillance (NHBS): Recommendations based on DC model.

INTRODUCTION: Social network strategies have been used by health departments to identify undiagnosed cases of HIV. Heterosexual cycle (HET4) of National HIV Behavioral Surveillance (NHBS) is a social network strategy implemented in jurisdictions. The main objectives of this research are to 1) evaluate the utility of the NHBS HET cycle data for network analysis; 2) to apply statistical analysis in support of previous HIV research, as well as to develop new research results focused on demographic variables and prevention/intervention with respect to heterosexual HIV risk; and 3) to employ NHBS data to inform policy with respect to the EHE plan. METHOD: We used data from the 2016 NHBS HET4 (DC). A total of 747 surveys were collected. We used the free social-network analysis package, GEPHI, for all network visualization using adjacency matrix representation. We additionally conducted logistic regression analysis to examine the association of selected variables with HIV status in three models representing 1) demographic and economic effects, 2) behavioral effects, and 3) prevention-intervention effects. RESULTS: The results showed 3% were tested positive. Seed 1 initiated the largest networks with 426 nodes (15 positives); seed 4 with 273 nodes (6 positives). Seed 3 had 35 nodes (2 positives). All 23 HIV diagnoses were recruited from 4 zip-codes across DC. The risk of testing positive was higher among people high-school dropouts (Relative Risk (RR) (25.645); 95 CI% 5.699, 115.987), unemployed ((4.267); 1.295, 14.064), returning citizens ((14.319); 4.593, 44.645). We also found in the final model higher association of pre-exposure prophylaxis (PrEP) awareness among those tested negative ((4.783); 1.042, 21.944) and HIV intervention in the past 12 months with those tested positive ((17.887); 2.350,136.135). CONCLUSION: The network visualization was used to address the primary aim of the analysis-evaluate the success of the implementation of the NHBS as a social network strategy to find new diagnoses. NHBS remains one of the strongest behavioral supplements for DC's HIV planning activities. As part of the evaluation process our analysis helps to understand the impact of demographic, behavioral, and prevention efforts on peoples' HIV status. We strongly recommend other jurisdictions use network visualizations to evaluate the efficacy in reaching hidden populations.

Examining Retention in HIV Care and HIV Suppression on Housing Services Intake at a Washington, DC Community Based Organization.

In Washington, DC, 2% of residents are living with HIV, with 15.3% of them experiencing homelessness. Additionally, over half of DC-area renters are paying over 30% of their income for housing. The primary objective of this study was to describe HIV outcomes at initial intake at Housing Counseling Services (HCS). This retrospective study included adults with HIV completing HCS intake between 2015 and 2018 and linked HCS data with DC Department of Health (DOH) HIV/AIDS, Hepatitis, STD, and TB Administration (HAHSTA) surveillance data. Proportions of individuals with retention in care (RIC) and viral suppression (VS) were compared across client subgroups using chi-square or rank sum tests. The sample of 734 participants was mostly male (67%), Non-Hispanic Black (89%), had MSM as the HIV transmission risk factor (44%) and had rental housing (60%). Most participants (634/734, 86%) were RIC at HCS intake. A majority of participants (477/621 or 77%) had VS at intake. Older age was associated with VS (p = 0.0007). Homeless individuals (with intake from the street) were less likely to be VS (4.8% vs. 11.1%, p < 0.0045). Our results suggest that PWH who have unstable housing or who are homeless may need additional support services for maintaining RIC and VS, as the proportion meeting those benchmarks was not at goal when they sought services at HCS.

Geographic Core Areas of Coinfections in Washington, District of Columbia: Recommendations for Planning Prevention-Intervention to Mitigate Human Immunodeficiency Virus Burden.

BACKGROUND: Research suggests that human immunodeficiency virus (HIV)-positive individuals with a sexually transmitted infection (STI) may be at increased risk of transmitting HIV to someone else through unprotected sex. The primary aim of the analysis is to identify the high-risk geographic areas of transmission of coinfections and factors that may be associated with poor outcomes of viral suppression within these higher-risk geographic areas, thus important in transmission prevention. METHODS: We used surveillance data reported by all providers and laboratories in the District of Columbia (DC). Applied discrete Poisson scan model in SaTScan to identify the geographic areas. The relative risk (RR) for the scan statistic was calculated based on events inside the cluster, and P values evaluated statistical significance. We used multinomial logistical regression to explore care and demographical characteristics associated with being virally unsuppressed within and outside the geographic areas. RESULTS: The coinfected areas (RR, >1; P < .001) were located in the tracts of central and southern DC. Black population (RR, 3.154 [95% confidence interval {CI}, 1.736-5.729]), age 13-19 years (RR, 4.598 [95% CI, 3.176-6.657]), repeat STIs (RR, 1.387 [95% CI, 1.096-1.754]), and not retained in care (RR, 2.546 [95% CI, 1.997-3.245]) were found to be at higher risk of being virally unsuppressed within the coinfected clusters. Those with unknown linkages were found to be at higher risk of being virally unsuppressed outside the coinfected clusters (RR, 5.162 [95% CI, 2.289-11.640]). CONCLUSIONS: This is DC's first effort to identify the geographic core areas of coinfections and factors that may be sustaining them. These results will be used by the health department to plan for prevention-intervention strategies. This model be replicated by any local jurisdiction similar.

A Spatial Approach for Ending the Human Immunodeficiency Virus Epidemic for the United States-A DC Model.

BACKGROUND: Mode of transmission-based hotspots is a smart approach to HIV mitigation, yet remains poorly evaluated and implemented in the United States. The primary aim was to identifying mode of transmission-based hotspots and populations at risk of lower viral suppression to assist in targeted planning and implementation of programs. METHODS: We implemented spatial statistics to identify global-local hotspots and regression analysis to find populations at risk of lower viral suppression within hotspots. Data were obtained from the District of Columbia's (DC's) active surveillance system, which were geocoded based on current residence address. RESULTS: The analysis identified 6001 HIV-positive men who have sex with men (MSM) and 6077 HIV-positive non-MSM (N = 12 078) living in DC at the end of 2018. The hotspots for MSM were central DC and non-MSM in south DC. Trends of viral suppression within MSM hotspots showed plateauing and, among non-MSM, showed decline. Regression analysis showed MSM aged 21-25 (RR: 3.199; 95% CI: 1.832-5.586) and not linked to care (8.592; 2.907-25.398) were at higher risk of being virally unsuppressed within the hotspots. For non-MSM we found those aged 12-18 (9.025; 3.314-2.581) and with unknown linkages (6.087; 3.346-13.848) were at higher risk of being virally unsuppressed within the hotspots. CONCLUSIONS: Our analysis provides a model that may be used by other jurisdictions to identify areas of priority and plan treatment-adherence programs using surveillance data. Attaining viral suppression is crucial in reducing new diagnoses; a spatial approach can be an important tool in Ending the HIV Epidemic.

Comparison of Clinical Outcomes of Persons Living With HIV by Enrollment Status in Washington, DC: Evaluation of a Large Longitudinal HIV Cohort Study.

BACKGROUND: HIV cohort studies have been used to assess health outcomes and inform the care and treatment of people living with HIV disease. However, there may be similarities and differences between cohort participants and the general population from which they are drawn. OBJECTIVE: The objective of this analysis was to compare people living with HIV who have and have not been enrolled in the DC Cohort study and assess whether participants are a representative citywide sample of people living with HIV in the District of Columbia (DC). METHODS: Data from the DC Health (DCDOH) HIV surveillance system and the DC Cohort study were matched to identify people living with HIV who were DC residents and had consented for the study by the end of 2016. Analysis was performed to identify differences between DC Cohort and noncohort participants by demographics and comorbid conditions. HIV disease stage, receipt of care, and viral suppression were evaluated. Adjusted logistic regression assessed correlates of health outcomes between the two groups. RESULTS: There were 12,964 known people living with HIV in DC at the end of 2016, of which 40.1% were DC Cohort participants. Compared with nonparticipants, participants were less likely to be male (68.0% vs 74.9%, P<.001) but more likely to be black (82.3% vs 69.5%, P<.001) and have a heterosexual contact HIV transmission risk (30.3% vs 25.9%, P<.001). DC Cohort participants were also more likely to have ever been diagnosed with stage 3 HIV disease (59.6% vs 47.0%, P<.001), have a CD4 <200 cells/µL in 2017 (6.2% vs 4.6%, P<.001), be retained in any HIV care in 2017 (72.9% vs 59.4%, P<.001), and be virally suppressed in 2017. After adjusting for demographics, DC Cohort participants were significantly more likely to have received care in 2017 (adjusted odds ratio 1.8, 95% CI 1.70-2.00) and to have ever been virally suppressed (adjusted odds ratio 1.3, 95% CI 1.20-1.40). CONCLUSIONS: These data have important implications when assessing the representativeness of patients enrolled in clinic-based cohorts compared with the DC-area general HIV population. As participants continue to enroll in the DC Cohort study, ongoing assessment of representativeness will be required.

Detecting Spatial Cores and Temporal Trends of Repeat STIs to Plan Pre-exposure Prophylaxis (PrEP) Scale-up in DC.

BACKGROUND: Repeat sexually transmitted infections (STIs) in DC primarily results from untreated sexual partners. This analysis aims to identify high-risk areas and temporal trends of repeat STIs for pre-exposure prophylaxis scale-up and STI mitigation in DC. METHODS: We identified repeat infections in the DC Department of Health STI and HIV data management systems, diagnosed from 2014 to 2018. The cases were geocoded and aggregated by census tracts. Poisson discrete scan statistic was implemented in SaTScan software to find clusters. Weighted moving average was used to compare temporal trends of repeat STIs. We used χ analysis to identify association with demographic variables. RESULTS: We identified 8535 repeat STIs from 2014 to 2018. Of these, 61.84% were among men, most cases were among blacks (34.75%) and 47.45% represented gonorrhea cases. The high-risk spatial clusters were identified as those tracts that had relative risk (relative risk > 1; P-value < 0.001). We identified one significant radius of risk covering tracts of wards 7 and 8 and parts of wards 5 and 6. We spotted positive temporal trends in cluster 1 and outside the cluster. We found significant associations of repeat STIs with gender (χ = 317.27, P < 0.001), age (χ = 539.26, P < 0.001), HIV coinfections (χ = 352.06, P < 0.001), and year of diagnoses (χ = 1.5, P < 0.01). CONCLUSIONS: Our findings indicate spatial disparities in DC for repeat STIs. This analysis is critical for pre-exposure prophylaxis planning, STI prevention strategies such as expedited partner therapies and condom distribution strategies in DC should prioritize the high-risk spatial cores.

Detecting spatial clusters of HIV and hepatitis coinfections.

BACKGROUND: People with HIV infection in the United States are often affected by chronic viral hepatitis. These coinfected people with either HBV or HCV are at increased risk for serious, life-threatening complications. Coinfections with viral hepatitis may also complicate the delivery of anti-retroviral therapy (ART) by escalating the risk of drug-related hepatoxicity. According to the Centers for Disease Control and Prevention (CDC), approximately 10 percent of people with HIV in the United States also have HBV, and 25 percent also have HCV coinfection. With the advent of highly active antiretroviral therapy (HAART) and the increased life-expectancy of HIV patients, clinicians are more likely to be confronted with issues related to co-infection and the management challenges that they present, especially in resource-limited settings. The purpose of this analysis was to identify geographical clusters of HIV- (HBV/HCV) co-infection and compared to the geographical clusters of not co-infected using DC, Department of Health surveillance data. The results of the analysis will be used to target resources to areas at risk. METHODS: HIV and Hepatitis surveillance data were matched among cases diagnosed between 1980 and 2016. HIV-hepatitis co-infected and the not co-infected spatial clusters were detected using discrete Poisson model. Kulldorff's spatial scan statistic method was implemented in the free software tool called SaTScan which has been widely adopted for detecting disease cluster. The analysis was conducted by tracts, but for visualization, ease of interpretation and assist in policy making the tract map was overlaid with the ward map using ArcGIS 10.5.1. RESULTS: Between 1980 and 2016, there were 12,965 diagnosed cases of HIV, of which 2,316 HIV/Hepatitis matches were identified. Of the 2316 co-infected people living in DC, 25 percent (N = 590) of people had HBV, and 75 percent (N = 1,726) had HCV. Out of 12,965 diagnosed cases, remaining 10,649 did not have any co-infections (not co-infected). IDU (27.16 percent) and MSM (32.86 percent) were the highest mode of transmission for co-infected population. African-American were reported 83.64 percent (N = 1,937) among co-infection population. Three clusters were identified for both co-infected population in DC. The largest cluster radius for co-infected analysis covers wards 6, 7 and 8 as well as large parts of 2 and 5 (p < 0.001). Multiple clusters were identified for not co-infected population (p < 0.001). IDU (n = 450) was the highest mode of transmission for the co-infected clusters. For all clusters combined of not co-infected population highest mode of transmission were MSM (n = 2,534). This analysis also showed racial disparity, economic deprivation and lack of education were prominent in the co-infected clusters. CONCLUSION: We identified locations of high risk clusters where enhanced hepatitis and HIV prevention, treatment, and care can help combat the epidemic. The clusters radius expands into the neighboring state of Maryland as well. The findings from this analysis will be used to target area based public health policy and healthcare interventions for HIV-hepatitis. It is recommended based on the analysis that needle exchange programs can successfully control new HIV infections as well as hepatitis co-infections.

Cross-Jurisdictional Data Exchange Impact on the Estimation of the HIV Population Living in the District of Columbia: Evaluation Study.

BACKGROUND: Accurate HIV surveillance data are essential to monitor trends to help end the HIV epidemic. Owing to strict policies around data security and confidentiality, HIV surveillance data have not been routinely shared across jurisdictions except a biannual case-by-case review process to identify and remove duplicate cases (Routine Interstate Duplicate Review, RIDR). HIV surveillance estimates for the District of Columbia (DC) are complicated by migration and care seeking throughout the metropolitan area, which includes Maryland and Virginia. To address gaps in HIV surveillance data, health departments of DC, Maryland, and Virginia have established HIV surveillance data sharing agreements. Although the Black Box (a privacy data integration tool external to the health departments) facilitates the secure exchange of data between DC, Maryland, and Virginia, its previous iterations were limited by the frequency and scope of information exchanged. The health departments of DC, Maryland, and Virginia engaged in data sharing to further improve HIV surveillance estimates. OBJECTIVE: This study assessed the impact of cross-jurisdictional data sharing on the estimation of people living with HIV in DC and reduction of cases in the RIDR process. METHODS: Data sharing agreements established in 2014 allowed for the exchange of HIV case information (eg, current residential address) and laboratory information (eg, test types, result dates, and results) from the enhanced HIV/AIDS Reporting System (eHARS). Regular data exchanges began in 2017. The participating jurisdictions transferred data (via secure file transfer protocol) for individuals having a residential address in a partnering jurisdiction at the time of HIV diagnosis or evidence of receiving HIV-related services at a facility located in a partnering jurisdiction. The DC Department of Health compared the data received to DC eHARS and imported updated data that matched existing cases. Evaluation of changes in current residential address and HIV prevalence was conducted by comparing data before and after HIV surveillance data exchanges. RESULTS: After the HIV surveillance data exchange, an average of 396 fewer cases were estimated to be living in DC each year from 2012 to 2016. Among cases with a residential status change, 66.4% (1316/1982) had relocated to Maryland and 19.8% (392/1982) to Virginia; majority of these had relocated to counties bordering DC. Relocation in and out of DC differed by mode of transmission, race and ethnicity, age group, and gender. After data exchange, the volume of HIV cases needing RIDR decreased by 74% for DC-Maryland and 81% for DC-Virginia. CONCLUSIONS: HIV surveillance data exchange between the public health departments of DC, Maryland, and Virginia reduced the number of cases misclassified as DC residents and reduced the number of cases needing RIDR. Continued data exchanges will enhance the ability of DC Department of Health to monitor the local HIV epidemic.

Geographic patterns of poor HIV/AIDS care continuum in District of Columbia.

BACKGROUND: Concurrent with the UNAIDS 90-90-90 and NHAS plans, the District of Columbia (DC) launched its 90/90/90/50 plan (Plan) in 2015. The Plan proposes that by 2020, 90% of all DC residents will know their HIV status; 90% of residents living with HIV will be in sustained treatment; 90% of those in treatment will reach "Viral Suppression" and DC will achieve 50% reduction of new HIV cases. To achieve these goals targeted prevention strategies are imperative for areas where the relative risk (RR) of not being linked to care (NL), not retained in any care (NRC) and low viral suppression (NVSP) are highest in the District. These outcomes are denoted in this study as poor outcomes of HIV care continuum. This study applies the Bayesian model for RR for area specific random effects to identify the census tracts with poor HIV care continuum outcomes for DC. METHODS: This analysis was conducted using cases diagnosed from 2010 to 2015 and reported to the surveillance system from the District of Columbia Department of Health (DC DOH), HIV/AIDS, Hepatitis, STD and TB Administration. The jurisdictions of the District of Columbia is divided into 179 census tracts. It is challenging to plot sparse data in 'small' local administrative areas, characteristically which may have a single-count datum for each geographic area. Bayesian methods overcome this problem by assimilating prior information to the underlying RR, making the predicted RR estimates robust. RESULTS: The RR of NL is higher in 59 (33%) out of 179 census tracts in DC. The RR of NRC was high in 46 (26%) of the census tracts while 52 census tracts (29%) show a high risk of having NVSP among its residents. This study also identifies clear correlated heterogeneity or clustering is evident in the northern tracts of the district. CONCLUSION: The study finds census tracts with higher RR of poor linkage to care outcomes in the District. These results will inform the Plan which aims to increase targeted testing leading to early initiation of antiretroviral therapy. The uniqueness of this study lies in its translational scope where surveillance data can be used to inform local public health programs and enhance the quality of health for the people with HIV.

Improving HIV Surveillance Data for Public Health Action in Washington, DC: A Novel Multiorganizational Data-Sharing Method.

BACKGROUND: The National HIV/AIDS Strategy calls for active surveillance programs for human immunodeficiency virus (HIV) to more accurately measure access to and retention in care across the HIV care continuum for persons living with HIV within their jurisdictions and to identify persons who may need public health services. However, traditional public health surveillance methods face substantial technological and privacy-related barriers to data sharing. OBJECTIVE: This study developed a novel data-sharing approach to improve the timeliness and quality of HIV surveillance data in three jurisdictions where persons may often travel across the borders of the District of Columbia, Maryland, and Virginia. METHODS: A deterministic algorithm of approximately 1000 lines was developed, including a person-matching system with Enhanced HIV/AIDS Reporting System (eHARS) variables. Person matching was defined in categories (from strongest to weakest): exact, very high, high, medium high, medium, medium low, low, and very low. The algorithm was verified using conventional component testing methods, manual code inspection, and comprehensive output file examination. Results were validated by jurisdictions using internal review processes. RESULTS: Of 161,343 uploaded eHARS records from District of Columbia (N=49,326), Maryland (N=66,200), and Virginia (N=45,817), a total of 21,472 persons were matched across jurisdictions over various strengths in a matching process totaling 21 minutes and 58 seconds in the privacy device, leaving 139,871 uniquely identified with only one jurisdiction. No records matched as medium low or low. Over 80% of the matches were identified as either exact or very high matches. Three separate validation methods were conducted for this study, and they all found ≥90% accuracy between records matched by this novel method and traditional matching methods. CONCLUSIONS: This study illustrated a novel data-sharing approach that may facilitate timelier and better quality HIV surveillance data for public health action by reducing the effort needed for traditional person-matching reviews without compromising matching accuracy. Future analyses will examine the generalizability of these findings to other applications.

The nationwide evaluation of fetal and infant mortality review (FIMR) programs: development and implementation of recommendations and conduct of essential maternal and child health services by FIMR programs.

OBJECTIVE: An evaluation of fetal and infant mortality review (FIMR) programs nationwide was conducted to characterize their unique role in improving the system of perinatal health care. The aim of this paper is to examine intermediate outcomes of the FIMR, in particular the development and implementation of recommendations produced by the FIMRs and the conduct of essential MCH services by the FIMRs. METHODS: We report on 74 FIMRs whose communities were selected for the nationwide evaluation and for whom we had data from the FIMR director or comparable respondent. We focus on the recommendations of the FIMRs and the essential maternal and child health (MCH) services conducted by the FIMRs as intermediate outcomes (or outputs) and then examine how selected characteristics of the FIMR may influence these. RESULTS: FIMRs developed recommendations on a broad range of topics but there were some areas for which nearly all programs had developed recommendations. The FIMRs relied primarily on strategies related to programs and practices, with few FIMRs reporting attention to policy-oriented approaches. Implementation of recommendations was high. Factors that influenced likelihood of implementing recommendations and conduct of essential MCH services included structure of the FIMR and training received by FIMR directors and staff. CONCLUSIONS: The focus of FIMR recommendations and the likelihood of implementation vary across FIMRs as does the conduct of essential MCH services. FIMR team structure and training of the director and staff are important areas to consider in efforts to maximize the impact of FIMR.

The relation of FIMR programs and other perinatal systems initiatives with maternal and child health activities in the community.

OBJECTIVES: To evaluate the association of the presence of a fetal and infant mortality review (FIMR) program, other perinatal systems initiative (PSI), or both in a community with the performance of essential maternal and child health (MCH) services by local health departments (LHDs). METHODS: Data were obtained from telephone interviews with professionals from LHDs across the United States. Logistic regression was used to estimate the odds of a LHD conducting each essential MCH service in communities with and without FIMR programs or with and without PSIs, adjusted for geographic area. RESULTS: Of the 193 communities in the sample, 41 had only a FIMR program, 36 had only a PSI, 47 had both programs, and 69 had neither. The presence of a FIMR was related to greater performance of essential MCH services in LHDs in six areas: data assessment and analysis; client services and access; quality assurance and improvement; community partnerships and mobilization; policy development; and enhancement of capacity of the health care work force. Similar findings were noted for the same broad essential services for PSIs. The comparisons of LHDs in FIMR and non-FIMR communities, however, showed greater involvement of communities with a FIMR program in essential MCH services related to data collection and quality assurance than were found for comparisons of LHDs in communities with and without a PSI. The presence of a PSI was uniquely associated with conducting needs assessments for pregnant women and infants, participation in coalitions for infants, promoting access for uninsured women to private providers and involving local officials and agencies in health plans for both populations. When both programs were present, LHDs had a greater odds of engaging in essential MCH services related to assessment and monitoring of the health of the population, reporting on progress in meeting the health needs of pregnant women and infants, and presenting data to local political officials than when either program alone was in the community. CONCLUSIONS: Local health departments in communities with FIMR programs or PSIs appear to be more likely to conduct essential MCH services in the community. Some of these relations are unique to FIMR, particularly for data collection and quality assurance services, and some are unique to PSIs, for example those that involve interaction with other community agencies or groups. Performance of the essential MCH services also appears to be enhanced when both a FIMR program and a PSI are present in the community.

Local health department perspectives on linkages among birthing hospitals.

OBJECTIVES: To describe perinatal linkages among hospitals, changes in their numbers and their impact on relationships among high-risk providers in local communities. STUDY DESIGN: Data were obtained about the organization of perinatal services in 1996-1999 from a cross-sectional study evaluating fetal and infant mortality review (FIMR) programs nationwide. Geographic areas were sampled based on region, population density, and the presence of a FIMR. A local health department representative was interviewed in 76% (N=193) of eligible communities; 188 provided data about hospitals. RESULTS: Linkages among all hospitals were reported in 143 communities and with a subspecialty hospital in 122. All but 12 communities had a maternity hospital, and changes in the number of hospitals occurred in 49 communities. Decreases in the number of Level II hospitals were related to changes in relationships among providers of high-risk care for mothers and newborns; they were associated with changing relationships only for mothers in Level I hospitals. These relations were noted only where established provider relationships existed. CONCLUSIONS: Decreases in the number of maternity hospitals affect provider relationships in communities, but only where there are established linkages among hospitals.

Integrated perinatal health framework. A multiple determinants model with a life span approach.

BACKGROUND: Despite great strides in improving prenatal care utilization among American women, key perinatal indicators have remained stagnant or worsened in the past decade, and the United States continues to rank near the bottom compared to other developed countries. A new approach is needed if we are to achieve improvements in perinatal health. METHODS: To propose a new framework that integrates a "life span" approach with a multiple determinants model. RESULTS: We recognize that (1) powerful influences on outcome occur long before pregnancy begins; (2) pregnancy outcome is shaped by social, psychological, behavioral, environmental, and biological forces; and (3) the demography of pregnancy has changed dramatically in the last few decades with more women delaying their first birth. Approaches that simultaneously consider the entire life span as well as multiple determinants may need to be adopted. We propose a framework that integrates these approaches and is supported by the research literature. The life span perspective focuses attention toward the preconceptional and interconceptional periods as targets for intervention in improving perinatal health. The multiple determinants model distinguishes among concepts of disease, health and functioning, and well-being for both women and their offspring. CONCLUSIONS: Our intent is to influence how policymakers, public health professionals, clinicians, and researchers approach perinatal health.