Publications by authors named "Ramal Moonesinghe"

57 Publications

Telehealth Availability and Usage Among Medicare Beneficiaries During the COVID-19 Pandemic, October and November 2020.

J Public Health Manag Pract 2022 Jan-Feb 01;28(1):77-85

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (Ms Chang and Dr Truman), and Office of Genomics and Precision Public Health (Dr Moonesinghe), Centers for Disease Control and Prevention, Atlanta, Georgia.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000001448DOI Listing
November 2021

Racial and ethnic differences in COVID-19 hospitalizations by metropolitan status among Medicare beneficiaries, 1 January-31 December 2020.

J Public Health (Oxf) 2021 Oct 5. Epub 2021 Oct 5.

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention (CDC), Atlanta, GA, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/pubmed/fdab355DOI Listing
October 2021

COVID-19 Hospitalization by Race and Ethnicity: Association with Chronic Conditions Among Medicare Beneficiaries, January 1-September 30, 2020.

J Racial Ethn Health Disparities 2021 Jan 8. Epub 2021 Jan 8.

Office of the Director, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention (CDC), 1600 Clifton Rd., NE, Mail Stop US 8-6, Atlanta, GA, 30329-4027, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s40615-020-00960-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7793388PMC
January 2021

Differential Association of HIV Funding With HIV Mortality by Race/Ethnicity, United States, 1999-2017.

Public Health Rep 2020 Jul/Aug;135(1_suppl):149S-157S

1242 Office of the Director, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.

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 ( < .05) changes at joinpoints, and 2-sided 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/0033354920912716DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804047PMC
September 2020

Measuring the Magnitude of Health Inequality Between 2 Population Subgroup Proportions.

Am J Epidemiol 2020 09;189(9):987-996

In this paper, we evaluate 11 measures of inequality, d(p1, p2), between 2 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 0 if and only if |p1 - p2| = 0, and maximal when |p1 - p2| = 1. They are also symmetrical [d(p1, p2) = d(p2, p1)] and complement-invariant [d(p1, p2) = d(1 - p2, 1 - p1)]. To study intermeasure agreement, 5 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 2 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, we propose a standard measurement unit akin to a z score. For skewed underlying beta distributions, 4 of the 5 retained measures, once standardized, offer more conservative assessments of the magnitude of inequality than the absolute difference. We conclude 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 2 proportions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/aje/kwaa050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483981PMC
September 2020

Opioid-Related Diagnoses and Concurrent Claims for HIV, HBV, or HCV among Medicare Beneficiaries, United States, 2015.

J Clin Med 2019 Oct 24;8(11). Epub 2019 Oct 24.

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, GA 30329, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/jcm8111768DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912616PMC
October 2019

Prevalence and Cardiovascular Health Impact of Family History of Premature Heart Disease in the United States: Analysis of the National Health and Nutrition Examination Survey, 2007-2014.

J Am Heart Assoc 2019 07 13;8(14):e012364. Epub 2019 Jul 13.

3 Office of Public Health Genomics Centers for Disease Control and Prevention Atlanta GA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/JAHA.119.012364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662130PMC
July 2019

County-Level Socioeconomic Disparities in Use of Medical Services for Management of Infections by Medicare Beneficiaries With Diabetes-United States, 2012.

J Public Health Manag Pract 2019 Jul/Aug;25(4):E44-E54

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) (Ms Chang and Dr Truman), National Center for Chronic Disease Prevention and Health Promotion (Dr Beckles), and Office of Minority Health and Health Equity (Dr Moonesinghe), Centers for Disease Control and Prevention, Atlanta, Georgia.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000000800DOI Listing
June 2020

Racial/Ethnic Disparities in Mortality: Contributions and Variations by Rurality in the United States, 2012⁻2015.

Int J Environ Res Public Health 2019 02 2;16(3). Epub 2019 Feb 2.

Centers for Disease Control and Prevention, Office of Minority Health and Health Equity, 4770 Buford Highway, TW-3, Atlanta, GA 30341, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ijerph16030436DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6388242PMC
February 2019

Unequal Declines in Absolute and Relative Disparities in HIV Diagnoses Among Black Women, United States, 2008 to 2016.

Am J Public Health 2018 11;108(S4):S299-S303

At the time of the study, Hanna B. Demeke was with Oak Ridge Institute for Science and Education, National Center for HIV/AIDS, Viral hepatitis, STD, and TB Prevention (NCHHSTP), Centers for Disease Control and Prevention (CDC), Atlanta, GA. Anna S. Johnson is with the Division of HIV/AIDS Prevention (DHAP), NCHHSTP, CDC. Baohua Wu is with ICF International, DHAP. Ramal Moonesinghe is with the Office of Minority Health and Health Equity, CDC. Hazel D. Dean is with the Office of the Director, NCHHSTP, CDC. Hazel D. Dean is also a guest editor for this supplement issue.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2105/AJPH.2018.304641DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215380PMC
November 2018

Racial/Ethnic Health Disparities Among Rural Adults-United States, 2012-2015: MMWR Surveillance Summaries / November 17, 2017 / 66(23);1-9.

J Health Care Poor Underserved 2018 ;29(1):19-34

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1353/hpu.2018.0003DOI Listing
May 2019

The contribution of family history to the burden of diagnosed diabetes, undiagnosed diabetes, and prediabetes in the United States: analysis of the National Health and Nutrition Examination Survey, 2009-2014.

Genet Med 2018 10 25;20(10):1159-1166. Epub 2018 Jan 25.

Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, USA, Georgia.

Purpose: Given 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.

Methods: We 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.

Results: Using 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.

Conclusion: These 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/gim.2017.238DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6060023PMC
October 2018

Racial/Ethnic Health Disparities Among Rural Adults - United States, 2012-2015.

MMWR Surveill Summ 2017 11 17;66(23):1-9. Epub 2017 Nov 17.

Office of the Director, CDC, Atlanta, Georgia.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.15585/mmwr.ss6623a1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829953PMC
November 2017

Trends in Relative Inequalities in Measures of Favorable and Adverse Population Health Outcomes.

Epidemiology 2017 05;28(3):e23-e24

Office of Minority Health and Health Equity, Centers for Disease Control and Prevention, Atlanta, GA, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/EDE.0000000000000625DOI Listing
May 2017

Functional Characteristics of Health Coalitions in Local Public Health Systems: Exploring the Function of County Health Councils in Tennessee.

J Public Health Manag Pract 2017 Jul/Aug;23(4):404-409

Indiana University Bloomington School of Public Health, Bloomington, Indiana (Dr Barnes); Department of Public Health, University of Tennessee, Knoxville, Tennessee (Dr Erwin); Office of Minority Health and Health Equity, Centers for Disease Control and Prevention, Atlanta, Georgia (Dr Moonesinghe); Health Communication Science Office, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia (Ms Brooks); Division of Health Systems Management and Policy, University of Memphis School of Public Health, Memphis, Tennessee (Dr Carlton); and Office of Rural and Community Health and Community Partnerships, Division of Health Sciences, East Tennessee State University, Johnson City, Tennessee (Mr Behringer).

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000000477DOI Listing
April 2018

Response to Scanlan Concerning: Measurement of Health Disparities, Health Inequities, and Social Determinants of Health to Support the Advancement of Health Equity.

J Public Health Manag Pract 2016 Nov-Dec;22(6):614-5

Office of Minority Health and Health Equity Centers for Disease Control and Prevention Atlanta, Georgia National Center for Health Statistics Hyattsville, Maryland Office of Minority Health and Health Equity Centers for Disease Control and Prevention Atlanta, Georgia National Center for Health Statistics Hyattsville, Maryland.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000000494DOI Listing
August 2019

Measuring health disparities: a comparison of absolute and relative disparities.

PeerJ 2015 24;3:e1438. Epub 2015 Nov 24.

National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention , Atlanta, GA , United States.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.7717/peerj.1438DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662578PMC
December 2015

Measurement of Health Disparities, Health Inequities, and Social Determinants of Health to Support the Advancement of Health Equity.

J Public Health Manag Pract 2016 Jan-Feb;22 Suppl 1:S33-42

Office of Minority Health and Health Equity (Drs Penman-Aguilar, Moonesinghe, and Bouye) and National Center for Chronic Disease and Health Promotion (Dr Beckles), Centers for Disease Control and Prevention, Atlanta, Georgia; and National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland (Drs Talih and Huang).

Reduction of health disparities and advancement of health equity in the United States require high-quality data indicative of where the nation stands vis-à-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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000000373DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5845853PMC
February 2017

Vital signs: leading causes of death, prevalence of diseases and risk factors, and use of health services among Hispanics in the United States - 2009-2013.

MMWR Morb Mortal Wkly Rep 2015 May;64(17):469-78

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4584552PMC
May 2015

Trends in Disparity by Sex and Race/Ethnicity for the Leading Causes of Death in the United States-1999-2010.

J Public Health Manag Pract 2016 Jan-Feb;22 Suppl 1:S13-24

National Center for HIV/AIDS, Viral Hepatitis, STD, & TB Prevention (NCHHSTP) (Ms Chang and Dr Truman), Office of Minority Health and Health Equity (Dr Moonesinghe), and Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, Georgia (Dr Athar).

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0000000000000267DOI Listing
February 2017

Difference in health inequity between two population groups due to a social determinant of health.

Int J Environ Res Public Health 2014 Dec 16;11(12):13074-83. Epub 2014 Dec 16.

Office of Minority Health and Health Equity, Center for Disease Control and Prevention, 4770 Buford Highway, Mailstop K77, Atlanta, GA 30341, USA.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ijerph111213074DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4276663PMC
December 2014

Training racial and ethnic minority students for careers in public health sciences.

Am J Prev Med 2014 Nov 16;47(5 Suppl 3):S368-75. Epub 2014 Oct 16.

National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC, Atlanta, Georgia.

Background: A workforce that resembles the society it serves is likely to be more effective in improving health equity for racial and ethnic minorities in the U.S. Racial and ethnic minorities are underrepresented in the U.S. public health professions. Project Imhotep is operated by Morehouse College with funding and technical assistance from CDC. Imhotep trains racial and ethnic minority students for entry into graduate and professional training programs for careers in the public health sciences. The curriculum focuses on biostatistics, epidemiology, and occupational safety and health with practical training in statistical data analysis, scientific writing, and oral presentation skills.

Purpose: To describe the Imhotep program and highlight some of its outcomes.

Methods: Data were collected every year by self-administered questionnaire or follow-up telephone and e-mail interviews of students who participated in Imhotep during 1982-2010 and were followed through December 2013.

Results: Findings demonstrated that 100% of the 481 trained students earned bachelor's degrees; 73.2% earned graduate degrees (53% earned master's degrees, 11.1% earned medical degrees, and 7.3% earned other doctoral degrees); and 60% entered public health careers.

Conclusions: The Imhotep program has improved the representation of racial and ethnic minorities among public health professionals in the U.S. A diverse workforce involving Imhotep graduates could augment the pool of pubic health professionals who make strategic and tactical decisions around program design and resource allocation that impact health in the most affected communities.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.amepre.2014.07.028DOI Listing
November 2014

Differences in healthy life expectancy for the US population by sex, race/ethnicity and geographic region: 2008.

J Public Health (Oxf) 2015 Sep 30;37(3):470-9. Epub 2014 Aug 30.

Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.

Background: Healthy life expectancy (HLE) varies among demographic segments of the US population and by geography. To quantify that variation, we estimated the national and regional HLE for the US population by sex, race/ethnicity and geographic region in 2008.

Methods: National HLEs were calculated using the published 2008 life table and the self-reported health status data from the National Health Interview Survey (NHIS). Regional HLEs were calculated using the combined 2007-09 mortality, population and NHIS health status data.

Results: In 2008, HLE in the USA varied significantly by sex, race/ethnicity and geographical regions. At 25 years of age, HLE for females was 47.3 years and ∼2.9 years greater than that for males at 44.4 years. HLE for non-Hispanic white adults was 2.6 years greater than that for Hispanic adults and 7.8 years greater than that for non-Hispanic black adults. By region, the Northeast had the longest HLE and the South had the shortest.

Conclusions: The HLE estimates in this report can be used to monitor trends in the health of populations, compare estimates across populations and identify health inequalities that require attention.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/pubmed/fdu059DOI Listing
September 2015

Classification tree analysis of race-specific subgroups at risk for a central venous catheter-related bloodstream infection.

Jt Comm J Qual Patient Saf 2014 Mar;40(3):134-43

Background: Studies of racial disparities in patient safety events often do not use race-specific risk adjustment and do not account for reciprocal covariate interactions. These limitations were addressed by using classification tree analysis separately for black patients and white patients to identify characteristics that segment patients who have increased risks for a venous catheter-related bloodstream infection.

Methods: A retrospective, cross-sectional analysis of 5,236,045 discharges from 103 Florida acute hospitals in 2005-2009 was conducted. Hospitals were rank ordered on the basis of the black/white Patient Safety Indicator (PSI) 7 rate ratio as follows: Group 1 (white rate higher), Group 2, (equivalent rates), Group 3, (black rate higher), and Group 4, (black rate highest). Predictor variables included 26 comorbidities (Elixhauser Comorbidity Index) and demographic characteristics. Four separate classification tree analyses were completed for each race/hospital group.

Results: Individual characteristics and groups of characteristics associated with increased PSI 7 risk differed for black and white patients. The average age for both races was different across the hospital groups (p < .01). Weight loss was the strongest single delineator and common to both races. The black subgroups with the highest PSI 7 risk were Medicare beneficiaries who were either < or = 25.5 years without hypertension or < or = 39.5 years without hypertension but with an emergency or trauma admission. The white subgroup with the highest PSI 7 risk consisted of patients < or = 45.5 years who had congestive heart failure but did not have either hypertension or weight loss.

Discussion: Identifying subgroups of patients at risk for a rare safety event such as PSI 7 should aid effective clinical decisions and efficient use of resources and help to guide patient safety interventions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/s1553-7250(14)40017-5DOI Listing
March 2014

Health insurance coverage - United States, 2008 and 2010.

MMWR Suppl 2013 Nov;62(3):61-4

One out of four adults aged 19-64 years reported not having health insurance at some time during 2011, with a majority remaining uninsured for ≥1 year. In the first quarter of 2010, an estimated 59.1 million persons had no health insurance for at least part of the year, an increase from 58.7 million in 2009 and 56.4 million in 2008. The unemployment rate increased from 5.8% to 9.3% from 2008 to 2009, the largest 1-year increase on record. Losing or changing jobs was the primary reason persons experienced a gap in health insurance. Employment-based coverage for persons aged <65 years continued to erode for the ninth year in a row, falling 3.0 percentage points from 61.9% in 2008 to 58.9% in 2009. Persons aged 18-64 years with no health insurance during the preceding year were seven times as likely as those continuously insured to forgo needed health care because of cost.
View Article and Find Full Text PDF

Download full-text PDF

Source
November 2013

Disparity in race-specific comorbidities associated with central venous catheter-related bloodstream infection (AHRQ-PSI7).

Am J Med Qual 2013 Nov-Dec;28(6):525-32. Epub 2013 Mar 24.

1University of North Carolina at Charlotte, Charlotte, NC.

Studies of racial disparities in hospital-level patient safety outcomes typically apply a race-common approach to risk adjustment. Risk factors specific to a minority population may not be identified in a race-common analysis if they represent only a small percentage of total cases. This study identified patient comorbidities and characteristics associated with the likelihood of a venous catheter-related bloodstream infection (Agency for Healthcare Research and Quality Patient Safety Indicator 7 [PSI7]) separately for blacks and whites using race-specific logistic regression models. Hospitals were ranked by the racial disparity in PSI7 and segmented into 4 groups. The analysis identified both black- and white-specific risk factors associated with PSI7. Age showed race-specific reverse association, with younger blacks and older whites more likely to have a PSI7 event. These findings suggest the need for race-specific covariate adjustments in patient outcomes and provide a new context for examining racial disparities.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1177/1062860613480826DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5836730PMC
September 2014

Linear and non-linear associations of gonorrhea diagnosis rates with social determinants of health.

Int J Environ Res Public Health 2012 Sep 3;9(9):3149-65. Epub 2012 Sep 3.

Centers for Disease Control and Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Atlanta, GA 30333, USA.

Identifying how social determinants of health (SDH) influence the burden of disease in communities and populations is critically important to determine how to target public health interventions and move toward health equity. A holistic approach to disease prevention involves understanding the combined effects of individual, social, health system, and environmental determinants on geographic area-based disease burden. Using 2006-2008 gonorrhea surveillance data from the National Notifiable Sexually Transmitted Disease Surveillance and SDH variables from the American Community Survey, we calculated the diagnosis rate for each geographic area and analyzed the associations between those rates and the SDH and demographic variables. The estimated product moment correlation (PMC) between gonorrhea rate and SDH variables ranged from 0.11 to 0.83. Proportions of the population that were black, of minority race/ethnicity, and unmarried, were each strongly correlated with gonorrhea diagnosis rates. The population density, female proportion, and proportion below the poverty level were moderately correlated with gonorrhea diagnosis rate. To better understand relationships among SDH, demographic variables, and gonorrhea diagnosis rates, more geographic area-based estimates of additional variables are required. With the availability of more SDH variables and methods that distinguish linear from non-linear associations, geographic area-based analysis of disease incidence and SDH can add value to public health prevention and control programs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ijerph9093149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3499859PMC
September 2012

A multistate examination of partnership activity among local public health systems using the National Public Health Performance Standards.

J Public Health Manag Pract 2012 Sep-Oct;18(5):E14-23

Department of Applied Health Science, Indiana University School of Public Health-Bloomington, USA.

This study examines whether partnership-related measures in the second version of the National Public Health Performance Standards (NPHPS) are useful in evaluating level of activity as well as identifying latent constructs that exist among local public health systems (LPHSs). In a sample of 110 LPHSs, descriptive analysis was conducted to determine frequency and percentage of 18 partnership-related NPHPS measures. Principal components factor analysis was conducted to identify unobserved characteristics that promote effective partnerships among LPHSs. Results revealed that 13 of the 18 measures were most frequently reported at the minimal-moderate level (conducted 1%-49% of the time). Coordination of personal health and social services to optimize access (74.6%) was the most frequently reported measure at minimal-moderate levels. Optimal levels (conducted >75% of the time) were reported most frequently in 2 activities: participation in emergency preparedness coalitions and local health departments ensuring service provision by working with state health departments (67% and 61% of respondents, respectively) and the least optimally reported activity was review partnership effectiveness (4% of respondents). Factor analysis revealed categories of partnership-related measures in 4 domains: resources and activities contributing to relationship building, evaluating community leadership activities, research, and state and local linkages to support public health activities. System-oriented public health assessments may have questions that serve as proxy measures to examine levels of interorganizational partnerships. Several measures from the NPHPS were useful in establishing a national baseline of minimal and optimal activity levels as well as identifying factors to enhance the delivery of the 10 essential public health services among organizations and individuals in public health systems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1097/PHH.0b013e31822ca424DOI Listing
November 2012

Estimating the contribution of genetic variants to difference in incidence of disease between population groups.

Eur J Hum Genet 2012 Aug 15;20(8):831-6. Epub 2012 Feb 15.

Office of Minority Health and Health Disparities, Centers for Disease Control and Prevention, Atlanta, GA 30341, USA.

Genome-wide association studies have identified multiple genetic susceptibility variants to several complex human diseases. However, risk-genotype frequency at loci showing robust associations might differ substantially among different populations. In this paper, we present methods to assess the contribution of genetic variants to the difference in the incidence of disease between different population groups for different scenarios. We derive expressions for the contribution of a single genetic variant, multiple genetic variants, and the contribution of the joint effect of a genetic variant and an environmental factor to the difference in the incidence of disease. The contribution of genetic variants to the difference in incidence increases with increasing difference in risk-genotype frequency, but declines with increasing difference in incidence between the two populations. The contribution of genetic variants also increases with increasing relative risk and the contribution of joint effect of genetic and environmental factors increases with increasing relative risk of the gene-environmental interaction. The contribution of genetic variants to the difference in incidence between two populations can be expressed as a function of the population attributable risks of the genetic variants in the two populations. The contribution of a group of genetic variants to the disparity in incidence of disease could change considerably by adding one more genetic variant to the group. Any estimate of genetic contribution to the disparity in incidence of disease between two populations at this stage seems to be an elusive goal.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ejhg.2012.15DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3400729PMC
August 2012

Short report: Race and rickettsiae: a United States perspective.

Am J Trop Med Hyg 2011 Dec;85(6):1124-5

Rickettsial Zoonoses Branch, Division of Vectorborne Infectious Diseases, National Center for Emerging and Zoonotic Infectious Disease, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

US surveillance programs for Rocky Mountain spotted fever (RMSF), ehrlichiosis, and anaplasmosis collect demographic data on patients, including race and ethnicity. Reporting of these diseases among race groups is not uniform across the United States. Because a laboratory confirmation is required to meet the national surveillance case definition, reporting may be influenced by a patient's access to healthcare. Determining the association between race and ethnicity with incidence of rickettsial infections requires targeted, active surveillance.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.4269/ajtmh.2011.11-0462DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225164PMC
December 2011
-->