Rural HIV Prevalence and Service Availability in the United States: A Chartbook

This chartbook examines 2016 HIV prevalence and the availability of HIV prevention, testing, and treatment services across the rural-urban continuum and by US Census region. Publicly available county-level HIV prevalence data from the CDC and state-produced HIV surveillance reports were used to estimate HIV prevalence across the rural-urban continuum. HIV prevalence data include all diagnoses of HIV infection, with or without a stage 3 (AIDS) diagnosis. Geocoded data on organizations that provide prevention, testing, and treatment services related to HIV were obtained from the National Prevention Information Network. HIV prevalence is higher in urban counties than rural counties (399 per 100,000 compared with 149 per 100,000, respectively), with prevalence decreasing with increasing level of rurality. HIV prevalence in urban counties is higher than HIV prevalence in rural counties in all but two states (South Carolina and Hawaii). The Northeast has the highest HIV prevalence (485 per 100,000) followed by the South (429 per 100,000), West (302 per 100,000), and Midwest (205 per 100,000). Analyses of the availability of HIV-related services show that compared with urban counties, a smaller proportion of rural counties have organizations that provided HIV prevention, testing, and treatment services. The findings of this study may help inform policies that augment rural HIV prevention, diagnosis, treatment, and outbreak response efforts

Rural-Urban Residence and Mortality among Three Cohorts of U.S. Adults

Though U.S. life expectancy has increased over the past 50 years, this benefit has not been geographically uniform and certain rural persons and communities face a mortality gap. Rural residents experience a shorter life expectancy than urban residents, with higher mortality rates from specific causes such as chronic obstructive pulmonary diseases, coronary heart disease, and lung cancer. Overall, there are higher mortality rates among rural residents for all five leading causes of death – heart disease, stroke, cancer, unintentional injury, and chronic lower respiratory disease – as compared to urban residents. We sought to close gaps in our understanding of the rural-urban mortality disparity by conducting a time-to-event cohort analysis using the National Health Interview Survey linked to national death certificate data. We found the risk of death at any point in time was 10 percent higher for rural as compared with urban residents and increased over time. Also, leading causes of death and rural-urban differences shifted between birth cohorts. Our findings generally suggest that the overall mortality penalty in rural areas between 1997 and 2011 may have been driven by social determinants of health. The findings from our study may help to identify potential policy and practice interventions that may reduce the rural-urban mortality gap and lead to longer, healthier lives for rural populations. For more information about this study, please contact Dr. Erika Ziller ([email protected]

The Northern Border Region: A Health-Focused Landscape Analysis

The Northern Border Regional Commission State and Region Chartbooks compile county- and state-level data related to health and health care access for the Northern Border Region and the individual states of Maine, New Hampshire, New York, and Vermont. Topics covered in the chartbooks include demographic and socioeconomic characteristics, access to care, health outcomes, mortality rates, Health Professional Shortage Areas, and the location of Rural Health Clinics, Federally Qualified Health Centers, hospitals, and substance use treatment facilities. When data allow, we highlight the counties with the worse performance on a measure, compared with the rest of the counties in the Northern Border Region. These data are intended to inform initiatives to support health and health care, particularly in rural counties and counties served by the Northern Border Regional Commission. For more information, please contact Katherine Ahrens, Ph

Pediatric and Pregnancy-related Visits at Rural Health Clinics in 2018 among Medicaid/CHIP Enrollees in 20 States

Background: There is limited information on the extent to which Rural Health Clinics (RHC) provide pediatric and pregnancy-related services to individuals enrolled in state Medicaid/CHIP programs. Methods: We used a 100% sample of the 2018 Medicaid Demographic and Eligibility and Other Services Transformed Medicaid Statistical Information System (T-MSIS) Analytic Files for 20 states to estimate pediatric and pregnancy-related services to patients enrolled in state Medicaid/CHIP programs. Results: Among children and young adults enrolled in Medicaid/CHIP in 20 states, around 1 in 10 visited a RHC in 2018. For those living in rural areas, around 1 in 5 visited an RHC in 2018. States with the highest percentage of their pediatric population visiting an RHC at least once in 2018 were Vermont (32%), Mississippi (26%), South Dakota (22%), and Montana (20%). Among reproductive age women with pregnancy-related services in 2018, 1 in 25 had a pregnancy-related visit to an RHC in 2018. For those living in rural areas, this was approximately 1 in 11. States with the highest percentage of their pregnancy-related population visiting an RHC at least once in 2018 for a pregnancy-related visit were Mississippi (13%), Vermont (11%), Kentucky (9%), South Dakota (9%), and Montana (9%). The distribution of health services provided and medical conditions seen varied across states. Conclusion: Further work is needed to understand the key factors contributing to observed differences in the volume of RHC encounters by state, as well as the variation in health services provided and the medical conditions seen at RHCs. For more information on this study, please contact Katherine Ahrens ([email protected]

Vermont: A Health-Focused Landscape Analysis

The Northern Border Regional Commission State and Region Chartbooks compile county- and state-level data related to health and health care access for the Northern Border Region and the individual states of Maine, New Hampshire, New York, and Vermont. Topics covered in the chartbooks include demographic and socioeconomic characteristics, access to care, health outcomes, mortality rates, Health Professional Shortage Areas, and the location of Rural Health Clinics, Federally Qualified Health Centers, hospitals, and substance use treatment facilities. When data allow, we highlight the counties with the worse performance on a measure, compared with the rest of the counties in the Northern Border Region. These data are intended to inform initiatives to support health and health care, particularly in rural counties and counties served by the Northern Border Regional Commission. For more information, please contact Katherine Ahrens, Ph

New Hampshire: A Health-Focused Landscape Analysis

The Northern Border Regional Commission State and Region Chartbooks compile county- and state-level data related to health and health care access for the Northern Border Region and the individual states of Maine, New Hampshire, New York, and Vermont. Topics covered in the chartbooks include demographic and socioeconomic characteristics, access to care, health outcomes, mortality rates, Health Professional Shortage Areas, and the location of Rural Health Clinics, Federally Qualified Health Centers, hospitals, and substance use treatment facilities. When data allow, we highlight the counties with the worse performance on a measure, compared with the rest of the counties in the Northern Border Region. These data are intended to inform initiatives to support health and health care, particularly in rural counties and counties served by the Northern Border Regional Commission. For more information, please contact Katherine Ahrens, Ph

Accuracy of the Drug-Dependency Checkbox on the Maine Birth Certificate for Medicaid-covered Births, 2016-2020

Introduction: The accuracy of the drug-dependency checkbox on Maine birth certificates is unknown. Our objective was to compare the drug-dependency checkbox with information on substance use disorders (SUDs) documented in Medicaid claims. Methods: Using rule-based deterministic matching, we linked Medicaid enrollment information to Maine birth-record data between 2016 and 2020 (N = 58 584). Among the linked records (n = 27 448), we identified maternal SUD diagnoses during the 280 days before through 7 days after delivery using ICD-CM-9/10 diagnosis codes. We used the following hierarchy to create mutually exclusive SUD categories: opioid use disorder (OUD), cannabis use disorder without cocaine use disorder, and other SUD disorders (alcohol, cocaine, nicotine, or other). Results: Among women enrolled in Medicaid at the time of delivery, 12% had drug dependency indicated on their birth record and 34% had at least one SUD diagnosis recorded in their Medicaid claims. Among birth records with drug dependency indicated, 56% indicated OUD, 26% indicated cannabis use disorder without cocaine use disorder, 8% indicated other SUD, and 10% indicated no SUD. Among those without drug dependency indicated, the corresponding percentages were 4% for OUD, 9% for cannabis use disorder, 14% for other SUD, and 74% for no SUD. Discussion: Although diagnoses of OUD and cannabis use disorder were more common among birth records with a checked drug-dependency checkbox, reporting of drug dependency on birth records does not appear to accurately indicate SUD during pregnancy. Conclusions: Our findings suggest that the drug-dependency checkbox on Maine birth certificates may have limited value in identifying SUD during pregnancy

How Distributed Research Networks Work in Real Life

In spring 2020, Maine joined a 12-state distributed research network to analyze measures of opioid use disorder using state Medicaid data. Findings from this project, as well as the pros and cons of participating in a distributed research network, will be discussed

Pregnancy Loss History at First Parity and Selected Adverse Pregnancy Outcomes

PURPOSE: To evaluate the association between pregnancy loss history and adverse pregnancy outcomes. METHODS: Pregnancy history was captured during a computer-assisted personal interview for 21,277 women surveyed in the National Survey of Family Growth (1995-2013). History of pregnancy loss (\u3c20 weeks) at first parity was categorized in three ways: number of losses, maximum gestational age of loss(es), and recency of last pregnancy loss. We estimated risk ratios for a composite measure of selected adverse pregnancy outcomes (preterm, stillbirth, or low birthweight) at first parity and in any future pregnancy, separately, using predicted margins from adjusted logistic regression models. RESULTS: At first parity, compared with having no loss, having 3+ previous pregnancy losses (adjusted risk ratio (aRR) = 1.66 [95% CI = 1.13, 2.43]), a maximum gestational age of loss(es) at ≥10 weeks (aRR = 1.28 [1.04, 1.56]) or having experienced a loss 24+ months ago (aRR = 1.36 [1.10, 1.68]) were associated with increased risks of adverse pregnancy outcomes. For future pregnancies, only having a history of 3+ previous pregnancy losses at first parity was associated with increased risks (aRR = 1.97 [1.08, 3.60]). CONCLUSION: Number, gestational age, and recency of pregnancy loss at first parity were associated with adverse pregnancy outcomes in U.S. women