Risk Environments, Race/Ethnicity, and HIV Status in a Large Sample of People Who Inject Drugs in the United States.
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ABSTRACT:
SUBMITTER: Cooper HL
PROVIDER: S-EPMC4790920 | biostudies-other | 2016
REPOSITORIES: biostudies-other
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Project description:Background:The total population health benefits and costs of HIV preexposure prophylaxis (PrEP) for people who inject drugs (PWID) in the United States are unclear. Objective:To evaluate the cost-effectiveness and optimal delivery conditions of PrEP for PWID. Design:Empirically calibrated dynamic compartmental model. Data Sources:Published literature and expert opinion. Target Population:Adult U.S. PWID. Time Horizon:20 years and lifetime. Intervention:PrEP alone, PrEP with frequent screening (PrEP+screen), and PrEP+screen with enhanced provision of antiretroviral therapy (ART) for individuals who become infected (PrEP+screen+ART). All scenarios are considered at 25% coverage. Outcome Measures:Infections averted, deaths averted, change in HIV prevalence, discounted costs (in 2015 U.S. dollars), discounted quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios. Results of Base-Case Analysis:PrEP+screen+ART dominates other strategies, averting 26 700 infections and reducing HIV prevalence among PWID by 14% compared with the status quo. Achieving these benefits costs $253 000 per QALY gained. At current drug prices, total expenditures for PrEP+screen+ART could be as high as $44 billion over 20 years. Results of Sensitivity Analysis:Cost-effectiveness of the intervention is linear in the annual cost of PrEP and is dependent on PrEP drug adherence, individual transmission risks, and community HIV prevalence. Limitation:Data on risk stratification and achievable PrEP efficacy levels for U.S. PWID are limited. Conclusion:PrEP with frequent screening and prompt treatment for those who become infected can reduce HIV burden among PWID and provide health benefits for the entire U.S. population, but, at current drug prices, it remains an expensive intervention both in absolute terms and in cost per QALY gained. Primary Funding Source:National Institute on Drug Abuse.
| S-EPMC5118181 | biostudies-literature
Project description:BackgroundApproximately 16% of infections among those living with diagnosed HIV infection in the United States are attributable to injection drug use. Antiretrovirals (ARVs) are recommended for all infected persons to improve health and prevent transmission. Using data from National HIV Behavioral Surveillance, we evaluated changes in ARV use from 2009 to 2015 among HIV-positive people who inject drugs (PWID).MethodsPWID were recruited by respondent-driven sampling in 20 cities. ARV use was defined as self-reported use at the time of interview. Prevalence ratios measuring change in ARV use per 3-year increase in year were estimated using log-linked Poisson regression models with generalized estimating equations.ResultsARV use was 58% (319/548) in 2009, 67% (410/608) in 2012, and 71% (386/545) in 2015. In all 3 cycle years, a higher percentage of ARV treatment was observed among males, PWID of older age (≥50), and PWID with current health insurance. ARV use increased overall, with an adjusted relative increase of 8% per every 3-year increase in year (adjusted prevalence ratio 1.08, 95% confidence interval: 1.03 to 1.12). ARV use also increased among most subgroups.ConclusionsThese findings show progress in ARV treatment, although ARV coverage remains low compared with other populations at risk for HIV. Efforts to improve ARV coverage among PWIDs are needed.
| S-EPMC7836744 | biostudies-literature
Project description:Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution.We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation.We used a geospatial sound model to estimate census block group–level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006–2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index.Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3–47.8?dBA] and 42.3?dBA (IQR: 40.4–45.5?dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9?dBA (IQR: 44.7–48.5?dBA) and 44.0?dBA (IQR: 42.2–45.5?dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions.We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United States. https://doi.org/10.1289/EHP898
| S-EPMC5744659 | biostudies-literature
Project description:The relevance of race and ethnicity to genetics and medicine has long been a matter of debate. An emerging consensus holds that race and ethnicity are social constructs and thus poor proxies for genetic diversity. The goal of this study was to evaluate the relationship between race, ethnicity, and clinically relevant pharmacogenomic variation in cosmopolitan populations. We studied racially and ethnically diverse cohorts of 65,120 participants from the United States All of Us Research Program (All of Us) and 31,396 participants from the United Kingdom Biobank (UKB). Genome-wide patterns of pharmacogenomic variation-6311 drug response-associated variants for All of Us and 5966 variants for UKB-were analyzed with machine learning classifiers to predict participants' self-identified race and ethnicity. Pharmacogenomic variation predicts race/ethnicity with averages of 92.1% accuracy for All of Us and 94.3% accuracy for UKB. Group-specific prediction accuracies range from 99.0% for the White group in UKB to 92.9% for the Hispanic group in All of Us. Prediction accuracies are substantially lower for individuals who identified with more than one group in All of Us (16.7%) or as Mixed in UKB (70.7%). There are numerous individual pharmacogenomic variants with large allele frequency differences between race/ethnicity groups in both cohorts. Frequency differences for toxicity-associated variants predict hundreds of adverse drug reactions per 1000 treated participants for minority groups in All of Us. Our results indicate that race and ethnicity can be used to stratify pharmacogenomic risk in the US and UK populations and should not be discounted when making treatment decisions. We resolve the contradiction between the results reported here and the orthodoxy of race and ethnicity as non-genetic, social constructs by emphasizing the distinction between global and local patterns of human genetic diversity, and we stress the current and future limitations of race and ethnicity as proxies for pharmacogenomic variation.
| S-EPMC10383154 | biostudies-literature
Project description:Current evidence and professional guidance recommend sleeping between 7 and 9 h in a 24-h period for optimal health. The present study examines the association between sleep duration and mortality and assesses whether this association varies by racial/ethnic identity for a large and diverse sample of United States adults. We use data on 274,836 adults, aged 25 and older, from the 2004–2014 waves of the National Health Interview Survey (NHIS) linked to prospective mortality through 2015 (23,382 deaths). Cox proportional hazards models were used in multi-variable regressions to estimate hazard ratios for mortality by sleep duration and racial/ethnic identity, controlling for sociodemographic, socioeconomic, and psychological distress variables. We find elevated risks of mortality from any cause for adults who sleep less than 5 h or more than 9 h in a 24-h period after all adjustments. Further, we find evidence that these elevated risks for mortality are more pronounced for some racial/ethnic groups and less pronounced for others. Improved understanding of differences in sleep duration and sleep health can facilitate more effective and culturally-tailored interventions around sleep health, improving overall well-being and enhancing longevity. Highlights • Sleeping less than 5 h associates with higher mortality than sleeping 5–7 h.• Sleeping more than 9 h associates with higher mortality than sleeping less than 7 h.• Mortality risks associated with inadequate and excessive sleep are race/ethnic specific.
| S-EPMC9920264 | biostudies-literature
Project description:BackgroundIn a 2018 descriptive study, cancer incidence in children (age 0-19) in diagnosis years 2003 to 2014 was reported as being highest in New Hampshire and in the Northeast region.MethodsUsing the Cancer in North America (CiNA) analytic file, we tested the hypotheses that incidence rates in the Northeast were higher than those in other regions of the United States either overall or by race/ethnicity group, and that rates in New Hampshire were higher than the Northeast region as a whole.ResultsIn 2003 to 2014, pediatric cancer incidence was significantly higher in the Northeast than other regions of the United States overall and among non-Hispanic Whites and Blacks, but not among Hispanics and other racial minorities. However, there was no significant variability in incidence in the states within the Northeast overall or by race/ethnicity subgroup. Overall, statistically significantly higher incidence was seen in the Northeast for lymphomas [RR, 1.15; 99% confidence interval (CI), 1.10-1.19], central nervous system neoplasms (RR, 1.12; 99% CI, 1.07-1.16), and neuroblastoma (RR, 1.13; 99% CI, 1.05-1.21).ConclusionsPediatric cancer incidence is statistically significantly higher in the Northeast than in the rest of the United States, but within the Northeast, states have comparable incidence. Differences in cancer subtypes by ethnicity merit further investigation.ImpactOur analyses clarify and extend previous reports by statistically confirming the hypothesis that the Northeast has the highest pediatric cancer rates in the country, by providing similar comparisons stratified by race/ethnicity, and by assessing variability within the Northeast.
| S-EPMC9578755 | biostudies-literature
Project description:AimsTo examine the cost-effectiveness of hepatitis C virus (HCV) treatment of people who inject drugs (PWID), combined with medication-assisted treatment (MAT) and syringe-service programs (SSP), to tackle the increasing HCV epidemic in the United States.DesignHCV transmission and disease progression models with cost-effectiveness analysis using a health-care perspective.SettingRural Perry County, KY (PC) and urban San Francisco, CA (SF), USA. Compared with PC, SF has a greater proportion of PWID with access to MAT or SSP. HCV treatment of PWID is negligible in both settings.ParticipantsPWID data were collected between 1998 and 2015 from Social Networks Among Appalachian People, U Find Out, Urban Health Study and National HIV Behavioral Surveillance System studies.Interventions and comparatorThree intervention scenarios modeled: baseline-existing SSP and MAT coverage with HCV screening and treatment with direct-acting antiviral for ex-injectors only as per standard of care; intervention 1-scale-up of SSP and MAT without changes to treatment; and intervention 2-scale-up as intervention 1 combined with HCV screening and treatment for current PWID.MeasurementsIncremental cost-effectiveness ratios (ICERs) and uncertainty using cost-effectiveness acceptability curves. Benefits were measured in quality-adjusted life-years (QALYs).FindingsFor both settings, intervention 2 is preferred to intervention 1 and the appropriate comparator for intervention 2 is the baseline scenario. Relative to baseline, for PC intervention 2 averts 1852 more HCV infections, increases QALYS by 3095, costs $21.6 million more and has an ICER of $6975/QALY. For SF, intervention 2 averts 36 473 more HCV infections, increases QALYs by 7893, costs $872 million more and has an ICER of $11 044/QALY. The cost-effectiveness of intervention 2 was robust to several sensitivity analysis.ConclusionsHepatitis C screening and treatment for people who inject drugs, combined with medication-assisted treatment and syringe-service programs, is a cost-effective strategy for reducing hepatitis C burden in the United States.
| S-EPMC7751348 | biostudies-literature
Project description:Adverse health outcomes caused by extreme heat represent the most direct human health threat associated with the warming of the Earth's climate. Socioeconomic, demographic, health, land cover, and temperature determinants contribute to heat vulnerability; however, nationwide patterns of residential and race/ethnicity disparities in heat vulnerability in the United States are poorly understood. This study aimed to develop a Heat Vulnerability Index (HVI) for the United States; to assess differences in heat vulnerability across geographies that have experienced historical and/or contemporary forms of marginalization; and to quantify HVI by race/ethnicity. Principal component analysis was used to calculate census tract level HVI scores based on the 2019 population characteristics of the United States. Differences in HVI scores were analyzed across the Home Owners' Loan Corporation (HOLC) "redlining" grades, the Climate and Economic Justice Screening Tool (CEJST) disadvantaged versus non-disadvantaged communities, and race/ethnicity groups. HVI scores were calculated for 55,267 U.S. census tracts. Mean HVI scores were 17.56, 18.61, 19.45, and 19.93 for HOLC grades "A"-"D," respectively. CEJST-defined disadvantaged census tracts had a significantly higher mean HVI score (19.13) than non-disadvantaged tracts (16.68). The non-Hispanic African American or Black race/ethnicity group had the highest HVI score (18.51), followed by Hispanic or Latino (18.19). Historically redlined and contemporary CEJST disadvantaged census tracts and communities of color were found to be associated with increased vulnerability to heat. These findings can help promote equitable climate change adaptation policies by informing policymakers about the national distribution of place- and race/ethnicity-based disparities in heat vulnerability.
| S-EPMC9744626 | biostudies-literature
Project description:ImportanceThe prevalence of diabetes among Hispanic and Asian American subpopulations in the United States is unknown.ObjectiveTo estimate racial/ethnic differences in the prevalence of diabetes among US adults 20 years or older by major race/ethnicity groups and selected Hispanic and non-Hispanic Asian subpopulations.Design, setting, and participantsNational Health and Nutrition Examination Surveys, 2011-2016, cross-sectional samples representing the noninstitutionalized, civilian, US population. The sample included adults 20 years or older who had self-reported diagnosed diabetes during the interview or measurements of hemoglobin A1c (HbA1c), fasting plasma glucose (FPG), and 2-hour plasma glucose (2hPG).ExposuresRace/ethnicity groups: non-Hispanic white, non-Hispanic black, Hispanic and Hispanic subgroups (Mexican, Puerto Rican, Cuban/Dominican, Central American, and South American), non-Hispanic Asian and non-Hispanic Asian subgroups (East, South, and Southeast Asian), and non-Hispanic other.Main outcomes and measuresDiagnosed diabetes was based on self-reported prior diagnosis. Undiagnosed diabetes was defined as HbA1c 6.5% or greater, FPG 126 mg/dL or greater, or 2hPG 200 mg/dL or greater in participants without diagnosed diabetes. Total diabetes was defined as diagnosed or undiagnosed diabetes.ResultsThe study sample included 7575 US adults (mean age, 47.5 years; 52% women; 2866 [65%] non-Hispanic white, 1636 [11%] non-Hispanic black, 1952 [15%] Hispanic, 909 [6%] non-Hispanic Asian, and 212 [3%] non-Hispanic other). A total of 2266 individuals had diagnosed diabetes; 377 had undiagnosed diabetes. Weighted age- and sex-adjusted prevalence of total diabetes was 12.1% (95% CI, 11.0%-13.4%) for non-Hispanic white, 20.4% (95% CI, 18.8%-22.1%) for non-Hispanic black, 22.1% (95% CI, 19.6%-24.7%) for Hispanic, and 19.1% (95% CI, 16.0%-22.1%) for non-Hispanic Asian adults (overall P < .001). Among Hispanic adults, the prevalence of total diabetes was 24.6% (95% CI, 21.6%-27.6%) for Mexican, 21.7% (95% CI, 14.6%-28.8%) for Puerto Rican, 20.5% (95% CI, 13.7%-27.3%) for Cuban/Dominican, 19.3% (95% CI, 12.4%-26.1%) for Central American, and 12.3% (95% CI, 8.5%-16.2%) for South American subgroups (overall P < .001). Among non-Hispanic Asian adults, the prevalence of total diabetes was 14.0% (95% CI, 9.5%-18.4%) for East Asian, 23.3% (95% CI, 15.6%-30.9%) for South Asian, and 22.4% (95% CI, 15.9%-28.9%) for Southeast Asian subgroups (overall P = .02). The prevalence of undiagnosed diabetes was 3.9% (95% CI, 3.0%-4.8%) for non-Hispanic white, 5.2% (95% CI, 3.9%-6.4%) for non-Hispanic black, 7.5% (95% CI, 5.9%-9.1%) for Hispanic, and 7.5% (95% CI, 4.9%-10.0%) for non-Hispanic Asian adults (overall P < .001).Conclusions and relevanceIn this nationally representative survey of US adults from 2011 to 2016, the prevalence of diabetes and undiagnosed diabetes varied by race/ethnicity and among subgroups identified within the Hispanic and non-Hispanic Asian populations.
| S-EPMC6990660 | biostudies-literature
Project description: Not available
| S-EPMC9996638 | biostudies-literature