BACKGROUND: Genetic risk models could potentially be useful in identifying high-risk groups for the prevention of complex diseases. We investigated the performance of this risk stratification strategy by examining epidemiological parameters that impact the predictive ability of risk models. METHODS: We assessed sensitivity, specificity, and positive and negative predictive value for all possible risk thresholds that can define high-risk groups and investigated how these measures depend on the frequency of disease in the population, the frequency of the high-risk group, and the discriminative accuracy of the risk model, as assessed by the area under the receiver-operating characteristic curve (AUC). In a simulation study, we modeled genetic risk scores of 50 genes with equal odds ratios and genotype frequencies, and varied the odds ratios and the disease frequency across scenarios. We also performed a simulation of age-related macular degeneration risk prediction based on published odds ratios and frequencies for six genetic risk variants. RESULTS: We show that when the frequency of the high-risk group was lower than the disease frequency, positive predictive value increased with the AUC but sensitivity remained low. When the frequency of the high-risk group was higher than the disease frequency, sensitivity was high but positive predictive value remained low. When both frequencies were equal, both positive predictive value and sensitivity increased with increasing AUC, but higher AUC was needed to maximize both measures. CONCLUSIONS: The performance of risk stratification is strongly determined by the frequency of the high-risk group relative to the frequency of disease in the population. The identification of high-risk groups with appreciable combinations of sensitivity and positive predictive value requires higher AUC.

Background Family history reflects the complex interplay of genetic susceptibility and shared environmental exposures and is an important risk factor for obesity, diabetes, and heart and blood conditions (ODHB). However, the overlap in family history associations between various ODHBs has not been quantified. Methods and Results We assessed the association between a self-reported family history of ODHBs and their risk in the adult population (age ≥20 years) of the AoU (All of Us) Research Program, a longitudinal cohort study of diverse participants across the United States. We conducted a family history-wide association study to systematically assess the association of a first-degree family history of 15 ODHBs in AoU. We performed stratified analyses based on racial and ethnic categories, education, household income and gender minority status, and quantified associations by type of affected relatives. Of 125 430 participants, 76.8% reported a first-degree family history of any ODHB, most commonly hypertension (n=64 982, 51.8%), high cholesterol (49 753, 39.7%), and heart attack (29 618, 23.6%). We use the FamWAS method to estimate 225 familial associations among 15 ODHBs. The results include overlapping associations between family history of different types of cardiometabolic conditions (such as type 2 diabetes and coronary artery disease), and their risk factors (obesity, hypertension), where adults with a family history of 1 ODHB exhibited 1.1 to 5.6 times (1.5, on average) the odds of having a different ODHB. Conclusions Our findings inform the utility of family history data as a risk assessment and screening tool for the prevention of ODHBs and to provide additional insights into shared risk factors and pathogenic mechanisms.

OBJECTIVE: The aim was to estimate odds ratios of associations between family history of arthritis, osteoporosis, and carpal tunnel syndrome and prevalence in a real-world population, uncovering family histories of related conditions that may increase risk due to shared heritability, condition pathophysiology, or social/environmental factors. METHODS: Using data from 156,307 participants in the All of Us (AoU) Research Program, we examined associations between self-reported first-degree family history of 5 common types of arthritis (fibromyalgia, gout, osteoarthritis (OA), rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE)), osteoporosis, and carpal tunnel syndrome and prevalence. We evaluate associations across 7 conditions and performed stratified analyses by race and ethnicity, sex, socioeconomic differences, body mass index, and type of affected relative. RESULTS: Over 38% of AoU participants reported a family history of any arthritis, osteoporosis, or carpal tunnel syndrome. Adults with a family history of any arthritis, osteoporosis, and carpal tunnel syndrome exhibited 3.68 to 7.59 (4.90, on average) odds of having the same condition, and 0.70 to 2.10 (1.24, on average) odds of having a different condition. The strongest associations observed were between family history of OA and prevalence of OA (OR 7.59, 95%CI 7.32-7.88), and family history of SLE and prevalence of SLE (OR 6.34, 95%CI 5.17-7.74). We additionally uncover race and ethnicity and sex disparities in family history associations. CONCLUSION: Family history of several related conditions was associated with increased risk for arthritis, osteoporosis, and carpal tunnel syndrome, underscoring the importance of family history of related conditions for primary prevention.

Primary immunodeficiencies (PIs) are a group of diseases that increase susceptibility to infectious diseases. Few studies have examined the relationship between PI and COVID-19 outcomes. In this study, we used Premier Healthcare Database, which contains information on inpatient discharges, to analyze COVID-19 outcomes among 853 adult PI and 1,197,430 non-PI patients who visited the emergency department. Hospitalization, intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and death had higher odds in PI patients than in non-PI patients (hospitalization aOR: 2.36, 95% CI: 1.87-2.98; ICU admission aOR: 1.53, 95% CI: 1.19-1.96; IMV aOR: 1.41, 95% CI: 1.15-1.72; death aOR: 1.37, 95% CI: 1.08-1.74), and PI patients spent on average 1.91 more days in the hospital than non-PI patients when adjusted for age, sex, race/ethnicity, and chronic conditions associated with severe COVID-19. Of the largest four PI groups, selective deficiency of the immunoglobulin G subclass had the highest hospitalization frequency (75.2%). This large study of United States PI patients provides real-world evidence that PI is a risk factor for adverse COVID-19 outcomes.

Access and use of health care services are essential to health and well-being for people with HIV and HIV-related comorbidities. Health care use during the COVID-19 pandemic among Medicare beneficiaries (MBs) with concurrent HIV and depression has not been investigated. We used 2020 Medicare data to assess the percentage of MBs with claims for HIV and depression who also received hospitalization, outpatient diagnostic services, drug treatment, and outpatient procedures. We assessed person-level association between service receipt and HIV and depression, adjusting for known risk factors. MBs with claims for HIV and depression were more likely than those with neither claim to have claims for short-stay hospitalization, long-stay hospitalization, outpatient diagnostic services, prescription drugs, or outpatient procedures, supplies, and products. Non-White beneficiaries were more likely than White beneficiaries to be hospitalized but were less likely to receive drug treatment, outpatient diagnostic services, or outpatient procedures, supplies, and products during the pandemic. Significant disparities in health care use by race/ethnicity existed among MBs. Policymakers and practitioners can use these findings to implement public health policies and programs that reduce disparities in health care access and optimize use among vulnerable populations during a public health emergency.

IMPORTANCE: During the COVID-19 pandemic, US emergency department (ED) visits for psychiatric disorders (PDs) and drug overdoses increased. Psychiatric disorders and substance use disorders (SUDs) independently increased the risk of COVID-19 hospitalization, yet their effect together is unknown. OBJECTIVE: To assess how comorbid PD and SUD are associated with the probability of hospitalization among ED patients with COVID-19. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cross-sectional study analyzed discharge data for adults (age ≥18 years) with a COVID-19 diagnosis treated in 970 EDs and inpatient hospitals in the United States from April 2020 to August 2021. EXPOSURES: Any past diagnosis of (1) SUD from opioids, stimulants, alcohol, cannabis, cocaine, sedatives, or other substances and/or (2) PD, including attention-deficit/hyperactivity disorder (ADHD), anxiety, bipolar disorder, major depression, other mood disorder, posttraumatic stress disorder (PTSD), or schizophrenia. MAIN OUTCOMES AND MEASURES: The main outcome was any hospitalization. Differences in probability of hospitalization were calculated to assess its association with both PD and SUD compared with PD alone, SUD alone, or neither condition. RESULTS: O 274 219 ED patients with COVID-19 (mean [SD] age, 54.6 [19.1] years; 667 638 women [52.4%]), 18.6% had a PD (mean age, 59.0 years; 37.7% men), 4.6% had a SUD (mean age, 50.1 years; 61.7% men), and 2.3% had both (mean age, 50.4 years; 53.1% men). The most common PDs were anxiety (12.9%), major depression (9.8%), poly (≥2) PDs (6.4%), and schizophrenia (1.4%). The most common SUDs involved alcohol (2.1%), cannabis (1.3%), opioids (1.0%), and poly (≥2) SUDs (0.9%). Prevalence of SUD among patients with PTSD, schizophrenia, other mood disorder, or ADHD each exceeded 21%. Based on significant specific PD-SUD pairs (Q < .05), probability of hospitalization of those with both PD and SUD was higher than those with (1) neither condition by a weighted mean of 20 percentage points (range, 6 to 36; IQR, 16 to 25); (2) PD alone by 12 percentage points (range, -4 to 31; IQR, 8 to 16); and (3) SUD alone by 4 percentage points (range, -7 to 15; IQR, -2 to 7). Associations varied by types of PD and SUD. Substance use disorder was a stronger predictor of hospitalization than PD. CONCLUSIONS AND RELEVANCE: This study found that patients with both PD and SUD had a greater probability of hospitalization, compared with those with either disorder alone or neither disorder. Substance use disorders appear to have a greater association than PDs with the probability of hospitalization. Overlooking possible coexisting PD and SUD in ED patients with COVID-19 can underestimate the likelihood of hospitalization. Screening and assessment of both conditions are needed.

BACKGROUND: Changes in emergency department (ED) usage among US Medicare beneficiaries (MB) with fee-for-service claims for HIV, viral hepatitis, sexually transmitted diseases (STDs) or tuberculosis (TB) (HHST) services have not been assessed since the COVID-19 pandemic. METHODS: During 2006-20, we assessed the annual number of MB with each HHST per 1000 persons with ED claims for all conditions, and changes in demographic and geographic distribution of ED claimants for each HHST condition. RESULTS: Of all persons who attended an ED for any condition, 10.5 million (27.5%) were MB with ≥1 ED claim in 2006; that number (percentage) increased to 11.0 million (26.7%) in 2019 and decreased to 9.2 million (22.7%) in 2020; < 5 MB per 1000 ED population had HHST ED claims in 2020. The percentage increase in ED claims was higher for MB with STDs than for those with other HHST conditions, including a 10% decrease for MB with TB in 2020. CONCLUSIONS: Trends in ED usage for HHST conditions were associated with changes in demographic and geographic distribution among MB during 2006-20. Updated ED reimbursement policies and primary care practices among MB might improve prevention, diagnosis and treatment of HHST conditions in the future.

Published research provides minimal insights into variation by urban or rural residence of HIV infection risk and injection drug use. We used the 2020 Medicare claims data to assess the association of urban-rural residence and concurrent HIV infection and opioid use disorder (OUD), adjusted for demographic risk factors, among Medicare beneficiaries (MBs) with fee-for-service claims paid during 2020. Medicare beneficiaries with both HIV infection and OUD were more likely than those without to be aged ≤64 years, male, Black, residing in the U.S. Northeast, residing in an urban county, and to have one or more comorbid condition. Medicare beneficiaries who lived in urban counties had higher odds (adjusted odds ratio 4.04; 95% confidence interval 3.72, 4.39) of having HIV and OUD than those who lived in rural counties. Urban-rural residence was associated with concurrent HIV infection and OUD, independent of age, sex, race/ethnicity, and comorbidity among MBs with claims paid during 2020.

INTRODUCTION: Family history is an established risk factor for both cardiovascular disease (CVD) and diabetes; however, no study has presented population-based prevalence estimates of family histories of CVD and diabetes and examined their joint impact on prevalence of diabetes, CVD, cardiometabolic risk factors, and mortality risk. METHODS: We analyzed data from a representative sample of the US adult population including 29,440 participants from the National Health and Nutrition Examination Survey (2007-2018) and assessed self-reported first-degree family history of diabetes and CVD (premature heart disease before age of 50 years) as well as meeting criteria and/or having risk factors for CVD and diabetes. RESULTS: Participants with joint family history exhibit 6.5 greater odds for having both diseases and are diagnosed with diabetes 6.6 years earlier than participants without family history. Healthy participants without prevalent CVD or diabetes but with joint family history exhibit a greater prevalence of diabetes risk factors compared to no family history counterparts. Joint family history is associated with an increase in all-cause mortality, but with no interactive effect. CONCLUSION: Over 44% of the US adult population has a family history of CVD and/or diabetes that is comparable in risk to common cardiometabolic risk factors. This wide presence of high-risk family history and its simplicity of ascertainment suggests that clinical and public health efforts should collect and act on joint family history of CVD and diabetes to improve population efforts in the prevention and early detection of these common chronic diseases.

Disparities in COVID-19 death rates by race and ethnicity have been reported in the United States (1,2). In response to these disparities, preventive, medical care, and social service assistance programs were implemented to lessen disparities in COVID-19 outcomes, including grants to support state, tribal, local, and territorial health department responses (3). The potential impact of such efforts on annual changes in racial and ethnic disparities in mortality rates that identify COVID-19 as the underlying cause of death has not been previously reported. This analysis used U.S. provisional mortality data from death certificates collected by CDC's National Vital Statistics System (NVSS) to estimate changes in COVID-19-related age-adjusted death rates (AADRs) by race and ethnicity during 2020-2021. Compared with non-Hispanic multiracial persons (the group with the lowest death rate), significant decreases in AADR ratios occurred during 2020-2021 among non-Hispanic American Indian or Alaska Native (AI/AN) persons (34.0%), non-Hispanic Asian (Asian) persons (37.6%), non-Hispanic Black or African American (Black) persons (40.2%), Hispanic persons (37.1%), and non-Hispanic White (White) persons (14%); a non-statistically significant 7.2% increase in AADR ratio occurred among non-Hispanic Native Hawaiian or other Pacific Islander (NH/OPI) persons. Despite reductions in AADR disparities from 2020 to 2021, large disparities in AADR by race and ethnicity remained in 2021. Providing effective preventive interventions, including vaccination and clinical care, to all communities in proportion to their need for these interventions is necessary to reduce racial and ethnic disparities in COVID-19 deaths.

CONTEXT: During the COVID-19 pandemic, demand for telehealth services increased to reduce disease exposure for patients and providers and to meet preexisting demand for physician services in health resource shortage areas. OBJECTIVE: To estimate self-reported telehealth availability, equipment for accessing telehealth, and telehealth usage among Medicare beneficiaries during the COVID-19 pandemic. DESIGN: We used data from the 2020 Medicare Current Beneficiary Survey (MCBS) COVID-19 Fall Supplement Public Use File to estimate the weighted percentages of beneficiaries who had (a) access to telehealth before or during COVID-19; (b) equipment for accessing telehealth; and (c) telehealth visits during COVID-19. We used logistic regression to examine sociodemographic factors associated with telehealth usage. PARTICIPANTS: Beneficiaries who participated in the MCBS COVID-19 Fall Supplements. RESULTS: During October and November 2020, telehealth appointments offered by providers were available to 63.8% (95% confidence interval [CI], 61.8-65.9) of Medicare beneficiaries who had accessed medical care by telephone or video. Among those, only 18.0% (95% CI, 16.1-19.9) had been offered telehealth before the pandemic. The majority of beneficiaries (92.2%; 95% CI, 91.2-93.1) had 1 or more types of equipment available for accessing telehealth, but only 44.9% (95% CI, 43.0-46.9) had had a telehealth visit since July 1, 2020. Older adults, minorities, those with a lower income, and non-English speakers had less availability of telehealth equipment. Patient characteristics were significantly (P < .05) associated with telehealth use, including age, sex, race/ethnicity, and equipment availability. CONCLUSION: Telehealth availability for Medicare beneficiaries increased substantially during the COVID-19 pandemic. Even with the improvement in telehealth offerings and use hastened by the pandemic, gaps in access and use still exist. Effectiveness and implementation research can find ways to close gaps in telehealth services between vulnerable and underrepresented populations and counterparts.

BACKGROUND: Risk for COVID-19 hospitalizations increases with increasing age and presence of underlying medical conditions. However, the burden has not been well-assessed in metropolitan and nonmetropolitan areas by race/ethnicity among Medicare population with chronic conditions. METHODS: We used the 2020 Medicare data to estimate COVID-19 hospitalization rates by race/ethnicity among Medicare beneficiaries for COVID-19 by metropolitan status and to assess the association of hospitalizations from COVID-19 with each of selected 29 chronic conditions for patients by metropolitan status and by race/ethnicity. RESULTS: The COVID-19 hospitalization rate was higher among beneficiaries residing in nonmetropolitan counties than those residing in metropolitan counties in 2020. Approximately 1 in 2 AI/AN, 1 in 3 NHB, Hispanic and A/PI, and 1 in 4 NHW beneficiaries with COVID-19 residing in nonmetropolitan counties were hospitalized. Beneficiaries with COVID-19 and chronic conditions were more likely to be hospitalized compared with those without chronic conditions. CONCLUSIONS: Hospitalization rates among beneficiaries with COVID-19 and chronic conditions were not distributed equally by race/ethnicity and by metropolitan status. Researchers, policymakers and practitioners can use these findings to explore more effective ways of reducing racial/ethnic and geographic disparities among minorities disproportionately affected by COVID-19 and are at highest risk of hospitalization.

OBJECTIVES: We assessed the association between hospitalization for illness from COVID-19 infection and chronic conditions among Medicare beneficiaries (MBs) with fee-for-service (FFS) claims by race and ethnicity for January 1-September 30, 2020. METHODS: We used 2020 monthly Medicare data from January 1-September 30, 2020, reported to the Centers for Medicare and Medicaid Services to compute hospitalization rates per 100 COVID-19 MBs with FFS claims who were hospitalized (ICD-10-CM codes: B97.29 before April 1, 2020; ICD-10-CM codes: U07.1 from April 1, 2020, onward) with or without selected chronic conditions. We used logistic regression to estimate adjusted odds ratios with 95% confidence intervals for association of person-level rate of being hospitalized with COVID-19 and each of 27 chronic conditions by race/ethnicity, controlling for age, sex, and urban-rural residence among MBs. RESULTS: COVID-19-related hospitalizations were associated with all selected chronic conditions, except osteoporosis and Alzheimer disease/dementia among COVID-19 MBs. The top five conditions with the highest odds for hospitalization among COVID-19 MBs were end-stage renal disease (adjusted odds ratios (aOR): 2.15; 95% CI: 2.10-2.21), chronic kidney disease (aOR: 1.54; 95% CI: 1.52-1.56), acute myocardial infarction (aOR: 1.45; 95% CI: 1.39-1.53), heart failure (aOR: 1.43; 95% CI: 1.41-1.44), and diabetes (aOR: 1.37; 95% CI: 1.36-1.39). CONCLUSIONS: Racial/ethnic disparities in hospitalization rate persist among MBs with COVID-19, and associations of COVID-19 hospitalization with chronic conditions differ among racial/ethnic groups in the USA. These findings indicate the need for interventions in racial/ethnic populations at the highest risk of being hospitalized with COVID-19.

OBJECTIVE: Federal funds have been spent to reduce the disproportionate effects of HIV/AIDS on racial/ethnic minority groups in the United States. We investigated the association between federal domestic HIV funding and age-adjusted HIV death rates by race/ethnicity in the United States during 1999-2017. METHODS: We analyzed HIV funding data from the Kaiser Family Foundation by federal fiscal year (FFY) and US age-adjusted death rates (AADRs) by race/ethnicity (Hispanic, non-Hispanic white, non-Hispanic black, and Asian/Pacific Islander and American Indian/Alaska Native [API+AI/AN]) from Centers for Disease Control and Prevention WONDER detailed mortality files. We fit joinpoint regression models to estimate the annual percentage change (APC), average APC, and changes in AADRs per billion US dollars in HIV funding, with 95% confidence intervals (CIs). For 19 data points, the number of joinpoints ranged from 0 to 4 on the basis of rules set by the program or by the user. A Monte Carlo permutation test indicated significant (P < .05) changes at joinpoints, and 2-sided t tests indicated significant APCs in AADRs. RESULTS: Domestic HIV funding increased from $10.7 billion in FFY 1999 to $26.3 billion in FFY 2017, but AADRs decreased at different rates for each racial/ethnic group. The average rate of change in AADR per US billion dollars was -9.4% (95% CI, -10.9% to -7.8%) for Hispanic residents, -7.8% (95% CI, -9.0% to -6.6%) for non-Hispanic black residents, -6.7% (95% CI, -9.3% to -4.0%) for non-Hispanic white residents, and -5.2% (95% CI, -7.8% to -2.5%) for non-Hispanic API+AI/AN residents. CONCLUSIONS: Increased domestic HIV funding was associated with faster decreases in age-adjusted HIV death rates for Hispanic and non-Hispanic black residents than for residents in other racial/ethnic groups. Increasing US HIV funding could be associated with decreasing future racial/ethnic disparities in the rate of HIV-related deaths.

Employee turnover is a major challenge facing the federal workforce, which has lost more employees to voluntary turnover than any other form of turnover. This study determined the associations between engagement, demographic factors, and voluntary turnover intention by analyzing 2015 Federal Employee Viewpoint Survey data. The findings indicate that employees with higher engagement levels are less likely to report an intention to leave their jobs than those with lower engagement levels. All engagement factors—perceptions of supervisors, leaders, and intrinsic work experience—are independently associated with turnover intention. Demographics also influenced turnover intention; being younger, male, and in a supervisory role and having a higher education level and shorter tenure were more likely to indicate turnover intention. Increasing employee engagement can have a positive effect on retaining a productive federal workforce. To retain an effective federal workforce, human capital management practices are needed to optimize factors that reduce turnover intention.

The paper evaluates 11 measures of inequality d(p1,p2) between two proportions p1 and p2, some of which are new to the health disparities literature. These measures are selected because they are continuous, nonnegative, equal to zero if and only if |p1-p2|=0, and maximal when |p1-p2|=1. They are also symmetric [d(p1,p2)=d(p2,p1)] and complement-invariant [d(p1,p2)=d(1-p2,1-p1)]. To study inter-measure agreement, five of the 11 measures, including the absolute difference, are retained, because they remain finite and are maximal if and only if |p1-p2|=1. Even when the two proportions are assumed to be drawn at random from a shared distribution-interpreted as the absence of an avoidable difference-the expected value of d(p1,p2) depends on the shape of the distribution (and the choice of d) and can be quite large. To allow for direct comparisons among measures, a standard measurement unit akin to a z-score is proposed. For skewed underlying beta distributions, four of the five retained measures, once standardized, offer more conservative assessments of the magnitude of inequality than the absolute difference. The paper concludes that, even for measures that share the highlighted mathematical properties, magnitude comparisons are most usefully assessed relative to an elicited or estimated underlying distribution for the two proportions.

Unsterile opioid injection increases risk for infection transmission, including HIV, hepatitis B virus (HBV), or hepatitis C virus (HCV). We assess prevalence of and risk factors associated with opioid overdose and infections with HIV, HBV, or HCV among Medicare beneficiaries with opioid-related fee-for-service claims during 2015. We conducted a cross-sectional analysis to estimate claims for opioid use and overdose and HIV, HBV, or HCV infections, using data from US Medicare fee-for-service claims. Beneficiaries with opioid-related claims had increased odds for HIV (2.3; 95% confidence interval (CI), 2.3-2.4), acute HBV (6.7; 95% CI, 6.3-7.1), chronic HBV (5.0; 95% CI, 4.7-5.4), acute HCV (9.6; 95% CI, 9.2-10.0), and chronic HCV (8.9; 95% CI, 8.7-9.1). Beneficiaries with opioid-related claims and for HIV, HBV, or HCV infection, respectively, had a 1.1-1.9-fold odds for having a claim for opioid overdose. Independent risk factors for opioid overdose and each selected infection outcome included age, sex, race/ethnicity, region, and residence in a high-vulnerability county. Having opioid-related claims and selected demographic attributes were independent, significant risk factors for having HIV, HBV, or HCV claims among US Medicare beneficiaries. These results might help guide interventions intended to reduce incidences of HIV, HCV, and HBV infections among beneficiaries with opioid-related claims.

Background Because family history is a known risk factor for heart disease, it is important to characterize its public health impact in terms of population prevalence of family history of heart disease, the burden of heart disease attributable to family history, and whether family history interacts with modifiable risk factors for heart disease. Methods and Results We used population data from NHANES (the National Health and Nutrition Examination Survey [2007-2014]) to measure the association of self-reported family history of premature heart disease ( FHPHD ) with cardiovascular disease (n=19 253) and to examine the association between cardiovascular health metrics and FHPHD (n=16 248). Using logistic regression and multivariable adjustment, family history odds ratios were 5.91 (95% CI , 3.34-10.44) for ages 20 to 39, 3.02 (95% CI, 2.41-3.79) for ages 40 to 59, and 1.87 (95% CI , 1.54-2.28) for age >/=60 for cardiovascular disease. The prevalence of cardiovascular disease for the population with a FHPHD (15.72%; 95% CI , 13.81-17.64) was more than double the prevalence of cardiovascular disease for those without a family history (6.25%; 95% CI , 5.82-6.69). Compared with participants with optimum cardiovascular health, the prevalence ratio for FHPHD was 1.98 (95% CI , 1.40-2.79) for those with inadequate cardiovascular health. Conclusions Millions of people who are at high risk of having cardiovascular disease could be identified using FHPHD . FHPHD can become an important component of public health campaigns that address modifiable risk factors that plan to reduce the overall risk of heart disease.

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.

OBJECTIVES: To assess changes in disparities of HIV diagnosis rates among Black women aged 18 years or older living in the United States. METHODS: We calculated estimated annual percent changes (EAPCs) in annual diagnosis rates, rate differences (absolute disparity), and rate ratios (relative disparity) for groups (total, US-born, and non-US-born) of Black women (referent was all White women) with diagnosed HIV infection, using data reported to the National HIV Surveillance System. RESULTS: Of 39 333 Black women who received an HIV diagnosis during 2008 to 2016, 21.4% were non-US-born. HIV diagnosis rates declined among all Black women, with the smallest decline among non-US-born groups (EAPC = -3.1; P </= .001). Absolute disparities declined for both US-born and non-US-born Black women; however, the relative disparity declined for Black women overall and US-born Black women, whereas it increased for non-US-born (including Caribbean- and Africa-born) Black women. CONCLUSIONS: Differences in disparities in HIV diagnoses exist between US-, and non-US-born (specifically Caribbean- and Africa-born) Black women. Accounting for the heterogeneity of the Black women's population is crucial in measuring and monitoring progress toward eliminating health disparities among Black women.

OBJECTIVE: To assess county-level socioeconomic disparities in medical service usage for infections among Medicare beneficiaries with diabetes (MBWDs) who had fee-for-service health insurance claims during 2012. DESIGN: We used Medicare claims data to calculate percentage of MBWDs with infections. SETTING: Medicare beneficiaries. PARTICIPANTS: We estimated the percentage of MBWDs who used medical services for each of 3 groups of infections by sex and quintiles of the prevalence of social factors in the person's county of residence: anatomic site-specific infections; pathogen-specific infections; and HHST infections (human immunodeficiency virus/acquired immunodeficiency syndrome, viral hepatitis, sexually transmitted diseases, and tuberculosis). MAIN OUTCOME MEASURES: Using quintiles of county-specific socioeconomic determinants, we calculated absolute and relative disparities in each group of infections for male and female MBWDs. We also used regression-based summary measures to estimate the overall average absolute and relative disparities for each infection group. RESULTS: Of the 4.5 million male MBWDs, 15.8%, 25.3%, and 2.7% had 1 or more site-specific, pathogen-specific, and HHST infections, respectively. Results were similar for females (n = 5.2 million). The percentage of MBWDs with 1 or more infections in each group increased as social disadvantage in the MBWDs' county of residence increased. Absolute and relative county-level socioeconomic disparities in receipt of medical services for 1 or more infections (site- or pathogen-specific) were 12.9 or less percentage points and 65.5% or less, respectively. For HHST infections, percentage of MBWDs having 1 or more HHST infections for persons residing in the highest quintile (Q5) was 3- to 4-fold higher (P < .001) than persons residing in the lowest quintile (Q1). CONCLUSIONS: Infection burden among MBWDs is generally associated with county-level contextual socioeconomic disadvantage, and the extent of health disparities varies by infection category, socioeconomic factor, and quintiles of socioeconomic disadvantage. The findings imply ongoing need for efforts to identify effective interventions for reducing county-level social disparities in infections among patients with diabetes.

OBJECTIVE: To assess county-level socioeconomic disparities in medical service usage for infections among Medicare beneficiaries with diabetes (MBWDs) who had fee-for-service health insurance claims during 2012. DESIGN: We used Medicare claims data to calculate percentage of MBWDs with infections. SETTING: Medicare beneficiaries. PARTICIPANTS: We estimated the percentage of MBWDs who used medical services for each of 3 groups of infections by sex and quintiles of the prevalence of social factors in the person's county of residence: anatomic site-specific infections; pathogen-specific infections; and HHST infections (human immunodeficiency virus/acquired immunodeficiency syndrome, viral hepatitis, sexually transmitted diseases, and tuberculosis). MAIN OUTCOME MEASURES: Using quintiles of county-specific socioeconomic determinants, we calculated absolute and relative disparities in each group of infections for male and female MBWDs. We also used regression-based summary measures to estimate the overall average absolute and relative disparities for each infection group. RESULTS: Of the 4.5 million male MBWDs, 15.8%, 25.3%, and 2.7% had 1 or more site-specific, pathogen-specific, and HHST infections, respectively. Results were similar for females (n = 5.2 million). The percentage of MBWDs with 1 or more infections in each group increased as social disadvantage in the MBWDs' county of residence increased. Absolute and relative county-level socioeconomic disparities in receipt of medical services for 1 or more infections (site- or pathogen-specific) were 12.9 or less percentage points and 65.5% or less, respectively. For HHST infections, percentage of MBWDs having 1 or more HHST infections for persons residing in the highest quintile (Q5) was 3- to 4-fold higher (P < .001) than persons residing in the lowest quintile (Q1). CONCLUSIONS: Infection burden among MBWDs is generally associated with county-level contextual socioeconomic disadvantage, and the extent of health disparities varies by infection category, socioeconomic factor, and quintiles of socioeconomic disadvantage. The findings imply ongoing need for efforts to identify effective interventions for reducing county-level social disparities in infections among patients with diabetes.

PurposeGiven the importance of family history in the early detection and prevention of type 2 diabetes, we quantified the public health impact of reported family health history on diagnosed diabetes (DD), undiagnosed diabetes (UD), and prediabetes (PD) in the United States.MethodsWe used population data from the National Health and Nutrition Examination Survey 2009-2014 to measure the association of reported family history of diabetes with DD, UD, and PD.ResultsUsing polytomous logistic regression and multivariable adjustment, family history prevalence ratios were 4.27 (confidence interval (CI): 3.57, 5.12) for DD, 2.03 (CI: 1.56, 2.63) for UD, and 1.26 (CI: 1.09, 1.44) for PD. In the United States, we estimate that 10.1 million DD cases, 1.4 million UD cases, and 3.9 million PD cases can be attributed to having a family history of diabetes.ConclusionThese findings confirm that family history of diabetes has a major public health impact on diabetes in the United States. In spite of the recent interest and focus on genomics and precision medicine, family health history continues to be an integral component of public health campaigns to identify persons at high risk for developing type 2 diabetes and early detection of diabetes to prevent or delay complications.GENETICS in MEDICINE advance online publication, 25 January 2018; doi:10.1038/gim.2017.238.

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.

CONTEXT: Partnerships are emerging as critically important vehicles for addressing health in local communities. Coalitions involving local health departments can be viewed as the embodiment of a local public health system. Although it is known that these networks are heavily involved in assessment and community planning activities, limited studies have evaluated whether health coalitions are functioning at an optimal capacity. OBJECTIVE: This study assesses the extent to which health coalitions met or exceeded expectations for building functional capacity within their respective networks. DESIGN: An evaluative framework was developed focusing on 8 functional characteristics of coalitions previously identified by Erwin and Mills. Twenty-nine indicators were identified that served as "proxy" measures of functional capacity within health coalitions. SETTING AND PARTICIPANTS: Ninety-three County Health Councils (CoHCs) in Tennessee. MAIN OUTCOME MEASURE(S): Diverse member representation; formal rules, roles, and procedures; open, frequent interpersonal communication; task-focused climate; council leadership; resources; active member participation; and external linkages were assessed to determine the level of functionality of CoHCs. Scores across all CoHCs were analyzed using descriptive statistics such as frequency distributions, measures of central tendency, and measures of variability. Data were analyzed using SAS 9.3. RESULTS: Of 68 CoHCs (73% response rate), the total mean score for the level of functional characteristics was 30.5 (median = 30.5; SD = 6.3; range, 18-44). Of the 8 functional characteristics, CoHCs met or exceeded all indicators associated with council leadership, tasked-focused climate, and external linkages. Lowest scores were for having a written communications plan, written priorities or goals, and opportunities for training. CONCLUSION: This study advances the research on health coalitions by establishing a process for quantifying the functionality of health coalitions. Future studies will be conducted to examine the association between health coalition functional capacity, local health departments' community health assessment and planning efforts, and changes in community health status.

Monitoring national trends in disparities in different diseases could provide measures to evaluate the impact of intervention programs designed to reduce health disparities. In the US, most of the reports that track health disparities provided either relative or absolute disparities or both. However, these two measures of disparities are not only different in scale and magnitude but also the temporal changes in the magnitudes of these measures can occur in opposite directions. The trends for absolute disparity and relative disparity could move in opposite directions when the prevalence of disease in the two populations being compared either increase or decline simultaneously. If the absolute disparity increases but relative disparity declines for consecutive time periods, the absolute disparity increases but relative disparity declines for the combined time periods even with a larger increase in absolute disparity during the combined time periods. Based on random increases or decreases in prevalence of disease for two population groups, there is a higher chance the trends of these two measures could move in opposite directions when the prevalence of disease for the more advantaged group is very small relative to the prevalence of disease for the more disadvantaged group. When prevalence of disease increase or decrease simultaneously for two populations, the increase or decrease in absolute disparity has to be sufficiently large enough to warrant a corresponding increase or decrease in relative disparity. When absolute disparity declines but relative disparity increases, there is some progress in reducing disparities, but the reduction in absolute disparity is not large enough to also reduce relative disparity. When evaluating interventions to reduce health disparities using these two measures, it is important to consider both absolute and relative disparities and consider all the scenarios discussed in this paper to assess the progress towards reducing or eliminating health disparities.

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.

CONTEXT: Temporal trends in disparities in the leading causes of death within and between US demographic subgroups indicate the need for and success of interventions to prevent premature death in vulnerable populations. Studies that report recent trends are limited and outdated. OBJECTIVE: To describe temporal trends in disparities in death rates by sex and race/ethnicity for the 10 leading causes of death in the United States during 1999-2010. DESIGN: We used underlying cause of death data and population estimates from the National Vital Statistics System to calculate age-adjusted death rates for the 10 leading causes of death during 1999-2010. We measured absolute and relative disparities by sex and race/ethnicity for each cause and year of death; we used weighted linear regression to test for significance of trends over time. RESULTS: Of the 10 leading causes of death, age-adjusted death rates by sex and race/ethnicity declined during 1999-2010 for 6 causes and increased for 4 causes. But sex and racial/ethnic disparities between groups persisted for each year and cause of death. In the US population, the decreasing trend during 1999-2010 was greatest for cerebrovascular disease (-36.5%) and the increasing trend was greatest for Alzheimer disease (52.4%). For each sex and year, the disparity in death rates between Asian/Pacific Islanders (API) and other groups varied significantly by cause of death. In 2010, the API-non-Hispanic black disparity was largest for heart disease, malignant neoplasms, cerebrovascular diseases, and nephritis; the API-American Indian/Alaska Native disparity was largest for unintentional injury, diabetes mellitus, influenza and pneumonia, and suicide; and the API-non-Hispanic white disparity was largest for chronic lower respiratory diseases and Alzheimer disease. CONCLUSIONS: Public health practitioners can use these findings to improve policies and practices and to evaluate progress in eliminating disparities and their social determinants in vulnerable populations.

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.