PROBLEM/CONDITION: In 2022, homicide was the second leading cause of death for Hispanic and Latino persons aged 15-24 years in the United States, the third leading cause of death for those aged 25-34 years, and the fourth leading cause of death for those aged 1-14 years. The majority of homicides of females, including among Hispanic and Latino persons, occur in the context of intimate partner violence (IPV). This report summarizes data from CDC's National Violent Death Reporting System (NVDRS) on IPV-related homicides of Hispanic and Latino persons in the United States. PERIOD COVERED: 2003-2021. DESCRIPTION OF SYSTEM: NVDRS collects data regarding violent deaths in the United States and links three sources: death certificates, coroner or medical examiner reports, and law enforcement reports. IPV-related homicides include both intimate partner homicides (IPHs) by current or former partners and homicides of corollary victims (e.g., children, family members, and new partners). Findings describe victim and suspect sex, age group, and race and ethnicity; method of injury; type of location where the homicide occurred; precipitating circumstances (i.e., events that contributed to the homicide); and other selected characteristics. Deaths related to each other (e.g., an ex-partner kills the former partner and their new partner) are linked into a single incident. State participation in NVDRS has expanded over time, and the number of states participating has varied by year; data from all available years (2003-2021) and U.S. jurisdictions (49 states, Puerto Rico, and the District of Columbia) were used for this report. Of the 49 states that collect data, all except California and Texas collect data statewide; Puerto Rico and District of Columbia data are jurisdiction wide. Florida was excluded because the data did not meet the completeness threshold for circumstances. RESULTS: NVDRS collected data on 24,581 homicides of Hispanic and Latino persons, and data from all available years (2003-2021) and U.S. jurisdictions (49 states, Puerto Rico, and the District of Columbia) were examined. Among homicides with known circumstances (n = 17,737), a total of 2,444 were classified as IPV-related (13.8%). Nearly half of female homicides (n = 1,453; 48.2%) and 6.7% (n = 991) of male homicides were IPV-related; however, among all Hispanic and Latino homicides, most victims were male (n = 20,627; 83.9%). Among the 2,319 IPV-related homicides with known suspects, 85% (n = 1,205) of suspects were current or former partners for female victims, compared with 26.2% (n = 236) for male Hispanic and Latino victims. Approximately one fifth (71 of 359 [19.8%]) of female IPV-related homicide victims of childbearing age with known pregnancy status were pregnant or ≤1 year postpartum. Approximately 5% of IPV-related homicide victims were identified as Black Hispanic or Latino persons (males: n = 67; 6.8%; females: n = 64; 4.4%). A firearm was used in the majority of Hispanic and Latino IPV-related homicides (males: n = 676; 68.2%; females: n = 766; 52.7%). INTERPRETATION: This report provides a detailed summary of NVDRS data on IPV-related homicides of Hispanic and Latino persons in the United States during 2003-2021. This report found heterogeneity of characteristics and circumstances of Hispanic and Latino IPV-related homicides. Whereas most Hispanic and Latino homicide victims were male, nearly 60% of Hispanic and Latino IPHs and IPV-related homicide victims were female. Additional research is needed to better understand the relation between IPHs and IPV-related homicides and race (distinct from ethnicity) and pregnancy. PUBLIC HEALTH ACTION: NVDRS provides critical and ongoing data on IPV-related homicides of Hispanic and Latino persons in the United States that can be used to identify existing strategies and develop new early intervention strategies to prevent IPV and the escalation of IPV to IPH. Strategies that have demonstrated promise in reducing rates of IPH include expanded availability of low-income housing units; sanctuary policies that outline the relation between immigration enforcement and law officers; state laws prohibiting firearm access to those subject to domestic violence restraining orders; improvement of community relations with police to implement risk-based interventions; and comprehensive social, economic, medical, and legal safety nets to create pathways out of abusive relationships, including for pregnant women. Community, local, state, and Federal leaders can combine data on IPV-related deaths and the best available evidence-based programming and policy to create community-engaged solutions that reflect the experience of their Hispanic and Latino communities, including historical and societal factors that increase risk for violence.

Social determinants of health (SDOH) are the conditions in which people are born, grow, live, work, and age that influence health outcomes, and structural and systemic drivers of health (SSD) are the social, cultural, political, and economic contexts that create and shape SDOH. With the integration of constructs from previous examples, we propose an SSD model that broadens the contextual effect of these driving forces or factors rooted in the Centers for Disease Control and Prevention's SDOH framework. Our SSD model (1) presents systems and structures as multidimensional, (2) considers 10 dimensions as discrete and intersectional, and (3) acknowledges health-related effects over time at different life stages and across generations. We also present an application of this SSD model to the housing domain and describe how SSD affect SDOH through multiple mechanisms that may lead to unequal resources, opportunities, and consequences contributing to a disproportionate burden of disease, illness, and death in the US population. Our enhanced SDOH framework offers an innovative and promising model for multidimensional, collaborative public health approaches toward achieving health equity and eliminating health disparities.

Health equity is the state in which everyone has a fair and just opportunity to attain their highest level of health, and no one is disadvantaged from achieving this potential because of social position or other socially determined circumstances.1 Science is a cornerstone of public health and central to efforts to achieve health equity. Science designed to generate knowledge to advance equity can improve population health and promote health for all members of society.2 In contrast, science and interventions not designed and implemented with equity in mind may inadvertently perpetuate or widen disparities, even while fostering overall improvements in population health.3 | Health equity science provides a conceptual framework for scientific endeavors that are designed and conducted to advance health equity.4 Health equity science investigates patterns and underlying contributors to health inequities and builds an evidence base that can guide action across the domains of the public health program, surveillance, policy, communication, and scientific inquiry to move toward eliminating, rather than simply documenting, inequities. | Building on extensive work in developing the importance and application of equity concepts in public health practice,5-7 we describe an equity-focused scientific framework and set of principles to guide public health efforts to fulfill the health equity mission of the Centers for Disease Control and Prevention (CDC).8

CONTEXT: The Centers for Disease Control and Prevention (CDC) has a long history of using high-quality science to drive public health action that has improved the health, safety, and well-being of people in the United States and globally. To ensure scientific quality, manuscripts authored by CDC staff are required to undergo an internal review and approval process known as clearance. During 2022, CDC launched a scientific clearance transformation initiative to improve the efficiency of the clearance process while ensuring scientific quality. PROGRAM: As part of the scientific clearance transformation initiative, a group of senior scientists across CDC developed a framework called the Domains of Excellence for High-Quality Publications (DOE framework). The framework includes 7 areas ("domains") that authors can consider for developing high-quality and impactful scientific manuscripts: Clarity, Scientific Rigor, Public Health Relevance, Policy Content, Ethical Standards, Collaboration, and Health Equity. Each domain includes multiple quality elements, highlighting specific key considerations within. IMPLEMENTATION: CDC scientists are expected to use the DOE framework when conceptualizing, developing, revising, and reviewing scientific products to support collaboration and to ensure the quality and impact of their scientific manuscripts. DISCUSSION: The DOE framework sets expectations for a consistent standard for scientific manuscripts across CDC and promotes collaboration among authors, partners, and other subject matter experts. Many aspects have broad applicability to the public health field at large and might be relevant for others developing high-quality manuscripts in public health science. The framework can serve as a useful reference document for CDC authors and others in the public health community as they prepare scientific manuscripts for publication and dissemination.

A public health practitioner's mission is to protect and promote the health of all people in all communities. Components of being successful in that mission include understanding who is at risk of negative outcomes, identifying effective actions to promote and protect health, and communicating information accordingly. Information must be scientifically rigorous, provide appropriate contextualizing information, and refer to and visually represent people through words and images in respectful ways. Public health communication objectives include that the audience accepts, understands, and acts on the information to protect and promote health. This article describes the impetus for, development of, and public health applications and implications of principles to guide communication efforts. CDC's Health Equity Guiding Principles for Inclusive Communication is a web-based resource published in August 2021 that offers - but does not mandate - guidance and recommendations for public health practice. The resource can help public health practitioners and their partners consider social inequities and diversity, think more inclusively about the people they serve, and adapt to the cultural, linguistic, environmental, and historical situation of each population or audience of focus. Users are encouraged to have conversations about the Guiding Principles as they plan and develop communication products and strategies in collaboration with communities and partners and build a shared vocabulary consistent with how communities and groups of focus see and understand themselves, because words matter. As the public health field renews its focus on shifting the paradigm toward equity, a language and narrative shift is a vital intervention.

From 2009 to 2018, overall suicide rates in the United States increased by 20.3% and increased by 43.5% among non-Hispanic American Indian and Alaska Native (AI/AN) communities. Combining years 2009 through 2018, suicide rates per 100 000 population among non-Hispanic AI/AN adolescents and young adults aged 15 to 34 years were 2 to 4 times higher than those of adolescents and young adults of other races and ethnicities. An estimated 14% to 27% of non-Hispanic AI/AN adolescents attempted suicide during that time. The elevated rates of suicidal behavior among non-Hispanic AI/AN adolescents and young adults reflect inequities in the conditions that create health. In this topical review, we describe school-based educational efforts that are driven by local AI/AN communities, such as the American Indian Life Skills curriculum, that teach stress and coping skills and show promise in reducing suicidal ideation attempts and fatalities among AI/AN adolescents. Using a social-determinants-of-health lens, we review the availability and quality of employment as an important influencer of suicidal behavior, as well as the role of the workplace as an environment for suicide prevention in AI/AN communities. Working with tribal, state, local, and federal colleagues, the public health community can implement programs known to be effective and create additional comprehensive strategies to reduce inequities and ultimately reduce suicide rates.

Established by the Centers for Disease Control and Prevention (CDC), the goal of the CDC Undergraduate Public Health Scholars (CUPS) program is to expose students underrepresented in public health and medicine to careers in public health; ultimately, increasing the membership of these groups in these fields including biomedical sciences. CDC implemented a retrospective outcome evaluation of 1,047 students who participated in the program from 2012 to 2017. Seventy-four percent (775) of students responded to the survey that captures their academic attainment and employment status, as well as their perception of the program’s and mentors’ influence on their career path. As of 2020, 639 (83.4%) of 775 participants have enrolled in an advanced degree program, with over 80% of 639 participants pursuing degrees in biomedical sciences, public health, or health care (BSPHHC)–related fields. Two thirds (374/566) of participants who reported they had ever been employed in a career position are working/have worked in BSPHHC-related fields. Overall, 77.4% (600) of 775 participants reported either the program or the mentors, or both were extremely or very influential to their career path. Students claimed the CUPS program had “opened their eyes,” inspired their interest, cultivated their passion for the field of public health, and fueled their drive to find solutions to and in social determinants of health and contribute to health equity. The opportunity to gain work and research experience through internship placements in CUPS has “opened doors” to first jobs and advanced education and training opportunities for many students. © 2021 Society for Public.

We aimed to assess Centers for Disease Control and Prevention (CDC) data systems on the extent of data collection on sex, sexual orientation, and gender identity as well as on age and race/ethnicity. Between March and September 2019, we searched 11 federal websites to identify CDC-supported or -led U.S. data systems active between 2015 and 2018. We searched the systems' website, documentation, and publications for evidence of data collection on sex, sexual orientation, gender identity, age, and race/ethnicity. We categorized each system by type (disease notification, periodic prevalence survey, registry/vital record, or multiple sources). We provide descriptive statistics of characteristics of the identified systems. Most (94.1%) systems we assessed collected data on sex. All systems collected data on age, and approximately 80% collected data on race/ethnicity. Only 17.7% collected data on sexual orientation and 5.9% on gender identity. Periodic prevalence surveys were the most common system type for collecting all the variables we assessed. While most U.S. public health data and monitoring systems collect data disaggregated by sex, age, and race/ethnicity, far fewer do so for sexual orientation or gender identity. Standards and examples exist to aid efforts to collect and report these vitally important data. Additionally important is increasing accessibility and appropriately tailored dissemination of reports of these data to public health professionals and other collaborators.

Native Hawaiian and Pacific Islander populations have been disproportionately affected by COVID-19 (1-3). Native Hawaiian, Pacific Islander, and Asian populations vary in language; cultural practices; and social, economic, and environmental experiences,(†) which can affect health outcomes (4).(§) However, data from these populations are often aggregated in analyses. Although data aggregation is often used as an approach to increase sample size and statistical power when analyzing data from smaller population groups, it can limit the understanding of disparities among diverse Native Hawaiian, Pacific Islander, and Asian subpopulations(¶) (4-7). To assess disparities in COVID-19 outcomes among Native Hawaiian, Pacific Islander, and Asian populations, a disaggregated, descriptive analysis, informed by recommendations from these communities,** was performed using race data from 21,005 COVID-19 cases and 449 COVID-19-associated deaths reported to the Hawaii State Department of Health (HDOH) during March 1, 2020-February 28, 2021.(††) In Hawaii, COVID-19 incidence and mortality rates per 100,000 population were 1,477 and 32, respectively during this period. In analyses with race categories that were not mutually exclusive, including persons of one race alone or in combination with one or more races, Pacific Islander persons, who account for 5% of Hawaii's population, represented 22% of COVID-19 cases and deaths (COVID-19 incidence of 7,070 and mortality rate of 150). Native Hawaiian persons experienced an incidence of 1,181 and a mortality rate of 15. Among subcategories of Asian populations, the highest incidences were experienced by Filipino persons (1,247) and Vietnamese persons (1,200). Disaggregating Native Hawaiian, Pacific Islander, and Asian race data can aid in identifying racial disparities among specific subpopulations and highlights the importance of partnering with communities to develop culturally responsive outreach teams(§§) and tailored public health interventions and vaccination campaigns to more effectively address health disparities.

We examined disparities in cumulative incidence of severe acute respiratory syndrome coronavirus 2 by race/ethnicity, age, and sex in the United States during January 1-October 1, 2020. Hispanic/Latino and non-Hispanic Black, American Indian/Alaskan Native, and Native Hawaiian/other Pacific Islander persons had a substantially higher incidence of infection than non-Hispanic White persons.

CONTEXT: Social and structural determinants of health (SDOH) have become part of the public health and health care landscape. The need to address SDOH is reinforced by morbidity and mortality trends, including a recent multiyear decrease in life expectancy and persistent health disparities. Leadership on SDOH-related efforts has come from public health, health care, private philanthropy, and nongovernmental entities. STRATEGY: The Centers for Disease Control and Prevention (CDC) has been addressing SDOH through both disease- or condition-specific programs and crosscutting offices. Guidance from public health partners in the field has led the CDC to consider more strategic approaches to incorporating SDOH into public health activities. IMPLEMENTATION: The CDC's crosscutting SDOH Workgroup responded to external recommendations to develop a specific vision and plan that aims to integrate SDOH into the agency's infrastructure. The group also sponsors CDC forums for sharing research and trainings on embedding SDOH in programs. The group created a Web site to centralize CDC SDOH research, data sources, practice tools, programs, and policies. PROGRESS: The CDC has shown strong leadership in prioritizing SDOH in recent years. Individual programs and crosscutting offices have developed various models aimed at ensuring that public health research and practice address SDOH. DISCUSSION: Building sustainable SDOH infrastructures in public health institutions that reach across multiple health topics and non-health organizations could increase chances of meeting public health morbidity and mortality reduction goals, including decreasing health disparities. Although public health priorities and socioeconomic trends will change over time, experience suggests that social and structural factors will continue to influence the public's health. The CDC and state, tribal, local, and territorial public health institutions have played important leadership roles in the system of community and service organizations that interface with communities they mutually serve to address SDOH. Continued capacity-building could help grow and sustain an SDOH infrastructure that advances this work.

Long-standing systemic social, economic, and environmental inequities in the United States have put many communities of color (racial and ethnic minority groups) at increased risk for exposure to and infection with SARS-CoV-2, the virus that causes COVID-19, as well as more severe COVID-19-related outcomes (1-3). Because race and ethnicity are missing for a proportion of reported COVID-19 cases, counties with substantial missing information often are excluded from analyses of disparities (4). Thus, as a complement to these case-based analyses, population-based studies can help direct public health interventions. Using data from the 50 states and the District of Columbia (DC), CDC identified counties where five racial and ethnic minority groups (Hispanic or Latino [Hispanic], non-Hispanic Black or African American [Black], non-Hispanic Asian [Asian], non-Hispanic American Indian or Alaska Native [AI/AN], and non-Hispanic Native Hawaiian or other Pacific Islander [NH/PI]) might have experienced high COVID-19 impact during April 1-December 22, 2020. These counties had high 2-week COVID-19 incidences (>100 new cases per 100,000 persons in the total population) and percentages of persons in five racial and ethnic groups that were larger than the national percentages (denoted as "large"). During April 1-14, a total of 359 (11.4%) of 3,142 U.S. counties reported high COVID-19 incidence, including 28.7% of counties with large percentages of Asian persons and 27.9% of counties with large percentages of Black persons. During August 5-18, high COVID-19 incidence was reported by 2,034 (64.7%) counties, including 92.4% of counties with large percentages of Black persons and 74.5% of counties with large percentages of Hispanic persons. During December 9-22, high COVID-19 incidence was reported by 3,114 (99.1%) counties, including >95% of those with large percentages of persons in each of the five racial and ethnic minority groups. The findings of this population-based analysis complement those of case-based analyses. In jurisdictions with substantial missing race and ethnicity information, this method could be applied to smaller geographic areas, to identify communities of color that might be experiencing high potential COVID-19 impact. As areas with high rates of new infection change over time, public health efforts can be tailored to the needs of communities of color as the pandemic evolves and integrated with longer-term plans to improve health equity.

The COVID-19 pandemic has disproportionately affected racial and ethnic minority groups in the United States. Whereas racial and ethnic disparities in severe COVID-19-associated outcomes, including mortality, have been documented (1-3), less is known about population-based disparities in infection with SARS-CoV-2, the virus that causes COVID-19. In addition, although persons aged <30 years account for approximately one third of reported infections,(§) there is limited information on racial and ethnic disparities in infection among young persons over time and by sex and age. Based on 689,672 U.S. COVID-19 cases reported to CDC's case-based surveillance system by jurisdictional health departments, racial and ethnic disparities in COVID-19 incidence among persons aged <25 years in 16 U.S. jurisdictions(¶) were described by age group and sex and across three periods during January 1-December 31, 2020. During January-April, COVID-19 incidence was substantially higher among most racial and ethnic minority groups compared with that among non-Hispanic White (White) persons (rate ratio [RR] range = 1.09-4.62). During May-August, the RR increased from 2.49 to 4.57 among non-Hispanic Native Hawaiian and Pacific Islander (NH/PI) persons but decreased among other racial and ethnic minority groups (RR range = 0.52-2.82). Decreases in disparities were observed during September-December (RR range = 0.37-1.69); these decreases were largely because of a greater increase in incidence among White persons, rather than a decline in incidence among racial and ethnic minority groups. NH/PI, non-Hispanic American Indian or Alaska Native (AI/AN), and Hispanic or Latino (Hispanic) persons experienced the largest persistent disparities over the entire period. Ensuring equitable and timely access to preventive measures, including testing, safe work and education settings, and vaccination when eligible is important to address racial/ethnic disparities.

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22(†)-July 3, 2020 were analyzed. The analysis was limited to 23 states(§) with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.

As of July 5, 2020, approximately 2.8 million coronavirus disease 2019 (COVID-19) cases and 130,000 COVID-19-associated deaths had been reported in the United States (1). Populations historically affected by health disparities, including certain racial and ethnic minority populations, have been disproportionally affected by and hospitalized with COVID-19 (2-4). Data also suggest a higher prevalence of infection with SARS-CoV-2, the virus that causes COVID-19, among persons experiencing homelessness (5). Safety-net hospitals,(dagger) such as Boston Medical Center (BMC), which provide health care to persons regardless of their insurance status or ability to pay, treat higher proportions of these populations and might experience challenges during the COVID-19 pandemic. This report describes the characteristics and clinical outcomes of adult patients with laboratory-confirmed COVID-19 treated at BMC during March 1-May 18, 2020. During this time, 2,729 patients with SARS-CoV-2 infection were treated at BMC and categorized into one of the following mutually exclusive clinical severity designations: exclusive outpatient management (1,543; 56.5%), non-intensive care unit (ICU) hospitalization (900; 33.0%), ICU hospitalization without invasive mechanical ventilation (69; 2.5%), ICU hospitalization with mechanical ventilation (119; 4.4%), and death (98; 3.6%). The cohort comprised 44.6% non-Hispanic black (black) patients and 30.1% Hispanic or Latino (Hispanic) patients. Persons experiencing homelessness accounted for 16.4% of patients. Most patients who died were aged >/=60 years (81.6%). Clinical severity differed by age, race/ethnicity, underlying medical conditions, and homelessness. A higher proportion of Hispanic patients were hospitalized (46.5%) than were black (39.5%) or non-Hispanic white (white) (34.4%) patients, a finding most pronounced among those aged <60 years. A higher proportion of non-ICU inpatients were experiencing homelessness (24.3%), compared with homeless patients who were admitted to the ICU without mechanical ventilation (15.9%), with mechanical ventilation (15.1%), or who died (15.3%). Patient characteristics associated with illness and clinical severity, such as age, race/ethnicity, homelessness, and underlying medical conditions can inform tailored strategies that might improve outcomes and mitigate strain on the health care system from COVID-19.

This review describes the context of health equity and options for integrating equity into public health practice. We first discuss how the conceptualization of health equity and how equity considerations in US public health practice have been shaped by multidisciplinary engagements. We then discuss specific ways to address equity in core public health functions, provide examples of relevant frameworks and promising strategies, and discuss conceptual and measurement issues relevant to assessing progress in moving toward health equity. Challenges and opportunities and their implications for future directions are identified. Expected final online publication date for the Annual Review of Public Health, Volume 41 is April 1, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The value of disaggregating non-metropolitan and metropolitan area deaths in illustrating place-based health effects is evident. However, how place interacts with characteristics such as race/ethnicity has been less firmly established. This study compared socioeconomic characteristics and age-adjusted mortality rates by race/ethnicity in six rurality designations and assessed the contributions of mortality rate disparities between non-Hispanic blacks (NHBs) and non-Hispanic whites (NHWs) in each designation to national disparities. Compared to NHWs, age-adjusted mortality rates for: (1) NHBs were higher for all causes (combined), heart disease, malignant neoplasms, and cerebrovascular disease; (2) American Indian and Alaska Natives were significantly higher for all causes in rural areas; (3) Asian Pacific islanders and Hispanics were either lower or not significantly different in all areas for all causes combined and all leading causes of death examined. The largest contribution to the U.S. disparity in mortality rates between NHBs and NHWs originated from large central metropolitan areas. Place-based variations in mortality rates and disparities may reflect resource, and access inequities that are often greater and have greater health consequences for some racial/ethnic populations than others. Tailored, systems level actions may help eliminate mortality disparities existing at intersections between race/ethnicity and place.

OBJECTIVE: Despite increasing diversity in the US population, substantial gaps in collecting data on race, ethnicity, primary language, and nativity indicators persist in public health surveillance and monitoring systems. In addition, few systems provide questionnaires in foreign languages for inclusion of non-English speakers. We assessed (1) the extent of data collected on race, ethnicity, primary language, and nativity indicators (ie, place of birth, immigration status, and years in the United States) and (2) the use of data-collection instruments in non-English languages among Centers for Disease Control and Prevention (CDC)-supported public health surveillance and monitoring systems in the United States. METHODS: We identified CDC-supported surveillance and health monitoring systems in place from 2010 through 2013 by searching CDC websites and other federal websites. For each system, we assessed its website, documentation, and publications for evidence of the variables of interest and use of data-collection instruments in non-English languages. We requested missing information from CDC program officials, as needed. RESULTS: Of 125 data systems, 100 (80%) collected data on race and ethnicity, 2 more collected data on ethnicity but not race, 26 (21%) collected data on racial/ethnic subcategories, 40 (32%) collected data on place of birth, 21 (17%) collected data on years in the United States, 14 (11%) collected data on immigration status, 13 (10%) collected data on primary language, and 29 (23%) used non-English data-collection instruments. Population-based surveys and disease registries more often collected data on detailed variables than did case-based, administrative, and multiple-source systems. CONCLUSIONS: More complete and accurate data on race, ethnicity, primary language, and nativity can improve the quality, representativeness, and usefulness of public health surveillance and monitoring systems to plan and evaluate targeted public health interventions to eliminate health disparities.

PROBLEM/CONDITION: Rural communities often have worse health outcomes, have less access to care, and are less diverse than urban communities. Much of the research on rural health disparities examines disparities between rural and urban communities, with fewer studies on disparities within rural communities. This report provides an overview of racial/ethnic health disparities for selected indicators in rural areas of the United States. REPORTING PERIOD: 2012-2015. DESCRIPTION OF SYSTEM: Self-reported data from the 2012-2015 Behavioral Risk Factor Surveillance System were pooled to evaluate racial/ethnic disparities in health, access to care, and health-related behaviors among rural residents in all 50 states and the District of Columbia. Using the National Center for Health Statistics 2013 Urban-Rural Classification Scheme for Counties to assess rurality, this analysis focused on adults living in noncore (rural) counties. RESULTS: Racial/ethnic minorities who lived in rural areas were younger (more often in the youngest age group) than non-Hispanic whites. Except for Asians and Native Hawaiians and other Pacific Islanders (combined in the analysis), more racial/ethnic minorities (compared with non-Hispanic whites) reported their health as fair or poor, that they had obesity, and that they were unable to see a physician in the past 12 months because of cost. All racial/ethnic minority populations were less likely than non-Hispanic whites to report having a personal health care provider. Non-Hispanic whites had the highest estimated prevalence of binge drinking in the past 30 days. INTERPRETATION: Although persons in rural communities often have worse health outcomes and less access to health care than those in urban communities, rural racial/ethnic minority populations have substantial health, access to care, and lifestyle challenges that can be overlooked when considering aggregated population data. This study revealed difficulties among non-Hispanic whites as well, primarily related to health-related risk behaviors. Across each population, the challenges vary. PUBLIC HEALTH ACTION: Stratifying data by different demographics, using community health needs assessments, and adopting and implementing the National Culturally and Linguistically Appropriate Services Standards can help rural communities identify disparities and develop effective initiatives to eliminate them, which aligns with a Healthy People 2020 overarching goal: achieving health equity.

The recent article by Kjellsson et al.1 discussed implications of the choice of attainment (“favorable”) and shortfall (“adverse”) relative inequalities using life expectancy and mortality as examples. They showed that these two relative inequalities could be different from each other and from absolute inequalities and concluded that choosing among the three measures requires a value judgment about their relative importance. However, it is important to illustrate the mathematical arguments that explain how and why attainment- and shortfall-relative measures give different answers to the question of interpreting whether the trends in these relative inequalities increased or decreased across a specific time period in some situations.

In 1985, the Report of the Secretary's Task Force on Black and Minority Health was published after the federal government convened the first group of health experts to analyze racial/ethnic health disparities among minorities. This analysis, also known as the Heckler report, revealed higher illness and death rates among minorities. The year 2015 marks the 30th anniversary of the Heckler Report and presents an opportunity to evaluate and continue to improve minority health at the national, state, tribal, territorial, and local levels.

Hispanics or Latinos constitute the largest racial/ethnic minority in the United States. They are also a very diverse population. Latino/Hispanic's health varies significantly for subgroups defined by national origin, race, primary language, and migration-related factors (place of birth, immigration status, years of residence in the United States). Most Hispanics speak Spanish at home, and one-third have limited English proficiency (LEP). There is growing awareness on the importance for population health monitoring programs to collect those data elements (Hispanic subgroup, primary language, and migration-related factors) that better capture Hispanics' diversity, and to provide language assistance (translation of data collection forms, interpreters) to ensure meaningful inclusion of all Latinos/Hispanics in national health monitoring. There are strong ethical and scientific reasons for such expansion of data collection by public health entities. First, expand data elements can help identify otherwise hidden Hispanic subpopulations' health disparities. This may promote a more just and equitable distribution of health resources to underserved populations. Second, language access is needed to ensure fair and legal treatment of LEP individuals in federally supported data collection activities. Finally, these strategies are likely to improve the quality and representativeness of data needed to monitor and address the health of all Latino/Hispanic populations in the United States.

In 2011, CDC published the first CDC Health Disparities and Inequalities Report (CHDIR) (1). This report examined health disparities in the United States associated with various characteristics, including race/ethnicity, sex, income, education, disability status, and geography. Health disparities were defined as "differences in health outcomes and their determinants between segments of the population, as defined by social, demographic, environmental, and geographic attributes" (1). Among other recommendations, the 2011 CHDIR emphasized the need to address health disparities with a dual intervention strategy focused on populations at greatest need and on improving the health of the U.S. population by making interventions available to everyone. The 2013 CHDIR updated the 2011 CHDIR and included additional reports on social and environmental determinants of health; the supplement emphasized the importance of multisectoral collaboration, highlighting the need for a comprehensive, community-driven approach to reducing health disparities in the United States (2). A follow-up report described five interventions that were shown to be effective or demonstrated promise for reducing health disparities (3). These publications have focused attention on the need to address health disparities in the United States (4), as well as on programs and interventions that address them. This supplement describes additional interventions that address particular disparities observed by race and ethnicity, socioeconomic status, geographic location, disability, and/or sexual orientation across a range of conditions, including asthma, infection with HIV and hepatitis A, use of colorectal cancer screening, youth violence, food security, and health-related quality of life.

Reduction of health disparities and advancement of health equity in the United States require high-quality data indicative of where the nation stands vis-a-vis health equity, as well as proper analytic tools to facilitate accurate interpretation of these data. This article opens with an overview of health equity and social determinants of health. It then proposes a set of recommended practices in measurement of health disparities, health inequities, and social determinants of health at the national level to support the advancement of health equity, highlighting that (1) differences in health and its determinants that are associated with social position are important to assess; (2) social and structural determinants of health should be assessed and multiple levels of measurement should be considered; (3) the rationale for methodological choices made and measures chosen should be made explicit; (4) groups to be compared should be simultaneously classified by multiple social statuses; and (5) stakeholders and their communication needs can often be considered in the selection of analytic methods. Although much is understood about the role of social determinants of health in shaping the health of populations, researchers should continue to advance understanding of the pathways through which they operate on particular health outcomes. There is still much to learn and implement about how to measure health disparities, health inequities, and social determinants of health at the national level, and the challenges of health equity persist. We anticipate that the present discussion will contribute to the laying of a foundation for standard practice in the monitoring of national progress toward achievement of health equity.

BACKGROUND: Hispanics and Latinos (Hispanics) are estimated to represent 17.7% of the U.S. POPULATION: Published national health estimates stratified by Hispanic origin and nativity are lacking. METHODS: Four national data sets were analyzed to compare Hispanics overall, non-Hispanic whites (whites), and Hispanic country/region of origin subgroups (Hispanic origin subgroups) for leading causes of death, prevalence of diseases and associated risk factors, and use of health services. Analyses were generally restricted to ages 18-64 years and were further stratified when possible by sex and nativity. RESULTS: Hispanics were on average nearly 15 years younger than whites; they were more likely to live below the poverty line and not to have completed high school. Hispanics showed a 24% lower all-cause death rate and lower death rates for nine of the 15 leading causes of death, but higher death rates from diabetes (51% higher), chronic liver disease and cirrhosis (48%), essential hypertension and hypertensive renal disease (8%), and homicide (96%) and higher prevalence of diabetes (133%) and obesity (23%) compared with whites. In all, 41.5% of Hispanics lacked health insurance (15.1% of whites), and 15.5% of Hispanics reported delay or nonreceipt of needed medical care because of cost concerns (13.6% of whites). Among Hispanics, self-reported smoking prevalences varied by Hispanic origin and by sex. U.S.-born Hispanics had higher prevalences of obesity, hypertension, smoking, heart disease, and cancer than foreign-born Hispanics: 30% higher, 40%, 72%, 89%, and 93%, respectively. CONCLUSION: Hispanics had better health outcomes than whites for most analyzed health factors, despite facing worse socioeconomic barriers, but they had much higher death rates from diabetes, chronic liver disease/cirrhosis, and homicide, and a higher prevalence of obesity. There were substantial differences among Hispanics by origin, nativity, and sex. IMPLICATIONS FOR PUBLIC HEALTH: Differences by origin, nativity, and sex are important considerations when targeting health programs to specific audiences. Increasing the proportions of Hispanics with health insurance and a medical home (patientcentered, team-based, comprehensive, coordinated health care with enhanced access) is critical. A feasible and systematic data collection strategy is needed to reflect health diversity among Hispanic origin subgroups, including by nativity.

The World Health Organization defines social determinants of health as "complex, integrated, and overlapping social structures and economic systems" that are responsible for most health inequities. Similar to the individual-level risk factors such as behavioral and biological risk factors that influence disease, we consider social determinants of health such as the distribution of income, wealth, influence and power as risk factors for risk of disease. We operationally define health inequity in a disease within a population due to a risk factor that is unfair and avoidable as the difference between the disease outcome with and without the risk factor in the population. We derive expressions for difference in health inequity between two populations due to a risk factor that is unfair and avoidable for a given disease. The difference in heath inequity between two population groups due to a risk factor increases with increasing difference in relative risks and the difference in prevalence of the risk factor in the two populations. The difference in health inequity could be larger than the difference in health outcomes between the two populations in some situations. Compared to health disparities which are typically measured and monitored using absolute or relative disparities of health outcomes, the methods presented in this manuscript provide a different, yet complementary, picture because they parse out the contributions of unfair and avoidable risk factors.

In 2011, CDC published the first CDC Health Disparities and Inequalities Report (CHDIR). This report examined health disparities in the United States associated with various characteristics, including race/ethnicity, sex, income, education, disability status, and geography. Health disparities were defined as "differences in health outcomes and their determinants between segments of the population, as defined by social, demographic, environmental, and geographic attributes". Among other recommendations, the 2011 CHDIR emphasized the need to address health disparities with a dual intervention strategy that focuses on populations at greatest need and improves the health of the general population by making interventions available to everyone. The 2013 CHDIR included updates on most topics from the 2011 CHDIR and on new topics. Compared with the 2011 CHDIR, the 2013 CHDIR included more reports on social and environmental determinants of health and emphasizes the importance of multisector collaboration. The 2013 CHDIR highlights the need for a "comprehensive, community-driven approach" to reducing health disparities in the United States.

Mixed-method designs are increasingly used in sexually transmitted infection (STI) and HIV prevention research. The authors designed a mixed-method approach and applied it to estimate and evaluate a predictor of continued female condom use (6+ uses, among those who used it at least once) in a 6-month prospective cohort study. The analysis included 402 women who received an intervention promoting use of female and male condoms for STI prevention and completed monthly quantitative surveys; 33 also completed a semistructured qualitative interview. The authors identified a qualitative theme (couples' female condom enjoyment [CFCE]), applied discriminant analysis techniques to estimate CFCE for all participants, and added CFCE to a multivariable logistic regression model of continued female condom use. CFCE related to comfort, naturalness, pleasure, feeling protected, playfulness, ease of use, intimacy, and feeling in control of protection. CFCE was associated with continued female condom use (adjusted odds ratio: 2.8, 95% confidence interval: 1.4-5.6) and significantly improved model fit (p < .001). CFCE predicted continued female condom use. Mixed-method approaches for "scaling up" qualitative findings from small samples to larger numbers of participants can benefit HIV and STI prevention research.

OBJECTIVES: There is currently no information on whether products evaluated in HIV microbicide trials affect the detection of the semen biomarkers prostate-specific antigen (PSA) or Y chromosome DNA. STUDY DESIGN: We tested (in vitro) dilutions of tenofovir (TFV), UC781 and the hydroxyethylcellulose (HEC) placebo gels using the Abacus ABAcard and the quantitative (Abbott Architect total PSA) assays for PSA and Y chromosome DNA by real-time polymerase chain reaction. RESULTS: TFV gel and the HEC placebo adversely affected PSA detection using the ABAcard but not the Abbott Architect total PSA assay. UC781 adversely affected both the ABAcard and Abbott Architect total PSA assays. While there were some quantitative changes in the magnitude of the signal, none of the products affected positivity of the Y chromosome assay. CONCLUSIONS: The presence of TFV or HEC gels did not affect quantitative PSA or Y chromosome detection in vitro. Confirmation of these findings is recommended using specimens obtained following use of these gels in vivo. IMPLICATIONS: Researchers should consider the potential for specific microbicides or any products to affect the particular assay used for semen biomarker detection. The ABAcard assay for PSA detection should not be used with TFV UC781, or HEC.

BACKGROUND: Although biological markers of women's exposure to semen from vaginal intercourse have been developed as surrogates for risk of infection or probability of pregnancy, data on their persistence time and clearance are limited. STUDY DESIGN: During 2006-2008, 52 couples were enrolled for three 14-day cycles of abstinence from vaginal sex during which women were exposed in the clinic to a specific quantity (10, 100 or 1000 muL) of their partner's semen. Vaginal swabs were collected before and at 1, 6, 12, 24, 48, 72 and 144 h after exposure for testing for prostate-specific antigen (PSA) and Y-chromosome DNA (Yc DNA). RESULTS: Immediately after exposure to 1000 muL of semen, the predicted sensitivity of being PSA positive was 0.96; this decreased to 0.65, 0.44, 0.21 and 0.07 at 6, 12, 24 and 48 h, respectively. Corresponding predicted sensitivity of being Yc DNA positive was 0.72 immediately postexposure; this increased to 0.76 at 1 h postexposure and then decreased to 0.60 (at 6 h), 0.63 (at 12 h), 0.49 (at 24 h), 0.21 (at 48 h), 0.17 (at 72 h) and 0.12 (at 144 h). CONCLUSIONS: Overall findings suggest that PSA may be more consistent as a marker of very recent exposure and that Yc DNA is more likely to be detected in the vagina after 12 h postexposure compared to PSA.