Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-14 (of 14 Records) |
Query Trace: Kirtland K[original query] |
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Outcomes of population surveillance data collection pilots and the behavioral risk factor surveillance system: What happens in Texas
Kirtland K , Garvin W , Yan T , Cavazos M , Berzofsky M , Freedner N , Muldavin B , Levine B , Gamble S , Town M . Surv Pract 2023 16 (1) 1-12 Declining response rates and rising costs have prompted the search for alternatives to traditional random-digit dialing (RDD) interviews. In 2021, three Behavioral Risk Factor Surveillance System (BRFSS) pilots were conducted in Texas: data collection using an RDD short message service (RDD SMS) text-messaging push-to-web pilot, an address-based push-to-web pilot, and an internet panel pilot. We used data from the three pilots and from the concurrent Texas BRFSS Computer Assisted Telephone Interview (CATI). We compared unweighted data from these four sources to demographic information from the American Community Survey (ACS) for Texas, comparing respondents' health information across the protocols as well as cost and response rates. Non-Hispanic White adults and college graduates disproportionately responded in all survey protocols. Comparing costs across protocols was difficult due to the differences in methods and overhead, but some cost comparisons could be made. The cost per complete for BRFSS/CATI ranged from $75 to $100, compared with costs per complete for address-based sampling ($31 to $39), RDD SMS ($12 to $20), and internet panel (approximately $25). There were notable differences among survey protocols and the ACS in age, race/ethnicity, education, and marital status. We found minimal differences in respondents' answers to heart disease-related questions; however, responses to flu vaccination questions differed by protocol. Comparable responses were encouraging. Properly weighted web-based data collection may help use data collected by new protocols as a supplement to future BRFSS efforts. |
Constructing state and national estimates of vaccination rates from immunization information systems
Raghunathan T , Kirtland K , Li J , White K , Murthy B , Lin XM , Harris L , Gibbs-Scharf L , Zell E . J Surv Stat Methodol 2023 11 (3) 688-712 Immunization Information Systems are confidential computerized population-based systems that collect data from vaccination providers on individual vaccinations administered along with limited patient-level characteristics. Through a data use agreement, Centers for Disease Control and Prevention obtains the individual-level data and aggregates the number of vaccinations for geographical statistical areas defined by the US Census Bureau (counties or equivalent statistical entities) for each vaccine included in system. Currently, 599 counties, covering 11 states, collect and report data using a uniform protocol. We combine these data with inter-decennial population counts from the Population Estimates Program in the US Census Bureau and several covariates from a variety of sources to develop model-based estimates for each of the 3,142 counties in 50 states and the District of Columbia and then aggregate to the state and national levels. We use a hierarchical Bayesian model and Markov Chain Monte Carlo methods to obtain draws from the posterior predictive distribution of the vaccination rates. We use posterior predictive checks and cross-validation to assess the goodness of fit and to validate the models. We also compare the model-based estimates to direct estimates from the National Immunization Surveys. © 2023 The Author(s). Published by Oxford University Press on behalf of the American Association for Public Opinion Research. All rights reserved. |
Estimating vaccination coverage for routinely recommended vaccines among children aged 2months and adolescents aged 13 through 17years using data from immunization information systems in the United States
Kirtland KA , Raghunathan T , Patel Murthy B , Li J , White K , Gibbs-Scharf L , Harris L , Zell ER . Vaccine 2022 40 (52) 7559-7570 OBJECTIVE: To use a model-based approach to estimate vaccination coverage of routinely recommended childhood and adolescent vaccines for the United States. METHODS: We used a hierarchical model with retrospective cohort data from eleven IIS jurisdictions, which contains vaccination records submitted by providers. Numerators included data from 2014 to 2019 at the county level for 2.4 million children at age 2 months and 14.4 million adolescents aged 13-17. Age-appropriate Census populations were used as denominators. Covariates associated with childhood and adolescent vaccinations were included in the model. Model-based estimates for each county were generated and aggregated to the national level to produce national vaccination coverage estimates and compared to National Immunization Survey (NIS) estimates of vaccination coverage. Trends of estimated vaccination coverage were compared between the model-based approach and NIS. RESULTS: From 2014 to 18, model-based national vaccination coverage estimates were within ten percentage points of NIS-Child vaccination coverage estimates for most vaccines among children at age 24 months. One notable difference was higher model-based vaccination coverage estimates for hepatitis B birth dose compared to NIS-Child coverage estimates. From 2014 to 19, model-based national vaccination coverage estimates were within ten percentage points of NIS-Teen vaccination coverage estimates for most vaccines among adolescents aged 13-17 years. Model-based vaccination coverage estimates were notably lower for varicella, MMR, and Hepatitis B compared to NIS-Teen coverage estimates among adolescents. Trends in estimates of national vaccination coverage were similar between model-based estimates for children and adolescents as compared to NIS-Child and NIS-Teen, respectively. CONCLUSIONS: A hierarchical model applied to data from IIS may be used to estimate coverage for routinely recommended vaccines among children and adolescents and allows for timely analyses of childhood and adolescent vaccines to quickly assess trends in vaccination coverage across the United States. Monitoring real-time vaccination coverage can help promote immunizations to protect children and adolescents against vaccine-preventable diseases. |
Influenza Vaccinations During the COVID-19 Pandemic - 11 U.S. Jurisdictions, September-December 2020.
Roman PC , Kirtland K , Zell ER , Jones-Jack N , Shaw L , Shrader L , Sprague C , Schultz J , Le Q , Nalla A , Kuramoto S , Cheng I , Woinarowicz M , Robison S , Robinson S , Meder K , Murphy A , Gibbs-Scharf L , Harris L , Murthy BP . MMWR Morb Mortal Wkly Rep 2021 70 (45) 1575-1578 Influenza causes considerable morbidity and mortality in the United States. Between 2010 and 2020, an estimated 9-41 million cases resulted in 140,000-710,000 hospitalizations and 12,000-52,000 deaths annually (1). As the United States enters the 2021-22 influenza season, the potential impact of influenza illnesses is of concern given that influenza season will again coincide with the ongoing COVID-19 pandemic, which could further strain overburdened health care systems. The Advisory Committee on Immunization Practices (ACIP) recommends routine annual influenza vaccination for the 2021-22 influenza season for all persons aged ≥6 months who have no contraindications (2). To assess the potential impact of the COVID-19 pandemic on influenza vaccination coverage, the percentage change between administration of at least 1 dose of influenza vaccine during September-December 2020 was compared with the average administered in the corresponding periods in 2018 and 2019. The data analyzed were reported from 11 U.S. jurisdictions with high-performing state immunization information systems.* Overall, influenza vaccine administration was 9.0% higher in 2020 compared with the average in 2018 and 2019, combined. However, in 2020, the number of influenza vaccine doses administered to children aged 6-23 months and children aged 2-4 years, was 13.9% and 11.9% lower, respectively than the average for each age group in 2018 and 2019. Strategic efforts are needed to ensure high influenza vaccination coverage among all age groups, especially children aged 6 months-4 years who are not yet eligible to receive a COVID-19 vaccine. Administration of influenza vaccine and a COVID-19 vaccine among eligible populations is especially important to reduce the potential strain that influenza and COVID-19 cases could place on health care systems already overburdened by COVID-19. |
Impact of the COVID-19 Pandemic on Administration of Selected Routine Childhood and Adolescent Vaccinations - 10 U.S. Jurisdictions, March-September 2020.
Patel Murthy B , Zell E , Kirtland K , Jones-Jack N , Harris L , Sprague C , Schultz J , Le Q , Bramer CA , Kuramoto S , Cheng I , Woinarowicz M , Robison S , McHugh A , Schauer S , Gibbs-Scharf L . MMWR Morb Mortal Wkly Rep 2021 70 (23) 840-845 After the March 2020 declaration of the COVID-19 pandemic in the United States, an analysis of provider ordering data from the federally funded Vaccines for Children program found a substantial decrease in routine pediatric vaccine ordering (1), and data from New York City and Michigan indicated sharp declines in routine childhood vaccine administration in these areas (2,3). In November 2020, CDC interim guidance stated that routine vaccination of children and adolescents should remain an essential preventive service during the COVID-19 pandemic (4,5). To further understand the impact of the pandemic on routine childhood and adolescent vaccination, vaccine administration data during March-September 2020 from 10 U.S. jurisdictions with high-performing* immunization information systems were assessed. Fewer administered doses of routine childhood and adolescent vaccines were recorded in all 10 jurisdictions during March-September 2020 compared with those recorded during the same period in 2018 and 2019. The number of vaccine doses administered substantially declined during March-May 2020, when many jurisdictions enacted stay-at-home orders. After many jurisdictions lifted these orders, the number of vaccine doses administered during June-September 2020 approached prepandemic baseline levels, but did not increase to the level that would have been necessary to catch up children who did not receive routine vaccinations on time. This lag in catch-up vaccination might pose a serious public health threat that would result in vaccine-preventable disease outbreaks, especially in schools that have reopened for in-person learning. During the past few decades, the United States has achieved a substantial reduction in the prevalence of vaccine-preventable diseases driven in large part to the ongoing administration of routinely recommended pediatric vaccines. These efforts need to continue even during the COVID-19 pandemic to reduce the morbidity and mortality from vaccine-preventable diseases. Health care providers should assess the vaccination status of all pediatric patients, including adolescents, and contact those who are behind schedule to ensure that all children are fully vaccinated. |
Frequency and cost of live vaccines administered too soon after prior live vaccine in children aged 12months through 6years, 2014-2017
Kirtland KA , Lin X , Kroger AT , Myerburg S , Rodgers L . Vaccine 2019 37 (46) 6868-6873 OBJECTIVE: To identify number of children who received live vaccines outside recommended intervals between doses and calculate corrective revaccination costs. METHODS: We analyzed >1.6 million vaccination records for children aged 12months through 6years from six immunization information system (IIS) Sentinel Sites from 2014-15 when live attenuated influenza vaccine (LAIV, FluMist(R) Quadrivalent) was recommended for use, and from 2016-17, when not recommended for use. Depending on the vaccine, insufficient intervals between live vaccine doses are less than 24 or 28days from a preceding live vaccine dose. Private and public purchase costs of vaccines were used to determine revaccination costs of live vaccine doses administered during the live vaccine conflict interval. Measles, mumps, rubella (MMR), varicella, combined MMRV, and LAIV were live vaccines evaluated in this study. RESULTS: Among 946,659 children who received at least one live vaccine dose from 2014-15, 4,873 (0.5%) received at least one dose too soon after a prior live vaccine (revaccination cost, $786,413) with a median conflict interval of 16days. Among 704,591 children who received at least one live vaccine dose from 2016-17, 1,001 (0.1%) received at least one dose too soon after a prior live vaccine (revaccination cost, $181,565) with a median conflict interval of 14days. The live vaccine most frequently administered outside of the recommended intervals was LAIV from 2014-15, and varicella from 2016-17. CONCLUSIONS: Live vaccine interval errors were rare (0.5%), indicating an adherence to recommendations. If all invalid doses were corrected by revaccination over the two time periods, the cost within the IIS Sentinel Sites would be nearly one million dollars. Provider awareness about live vaccine conflicts, especially with LAIV, could prevent errors, and utilization of clinical decision support functionality within IISs and Electronic Health Record Systems can facilitate better vaccination practices. |
Availability of the National Diabetes Prevention Program in United States counties, March 2017
Jayapaul-Philip B , Dai S , Kirtland K , Haslam A , Nhim K . Prev Chronic Dis 2018 15 E109 In the United States, 84.1 million adults are estimated to have prediabetes, a serious health condition in which blood sugar levels are higher than normal but not high enough for a diagnosis of diabetes (1). Prediabetes increases the risk for type 2 diabetes, heart disease, and stroke (1). Through the Centers for Disease Control and Prevention (CDC)-led National Diabetes Prevention Program (National DPP), people with prediabetes can learn to make practical, real-life changes that can reduce their risk for developing type 2 diabetes by as much as 58% (71% for people aged ≥60 years) (1). CDC is working to expand the lifestyle change program (LCP) across the country, via the National DPP (2). Given the large number of people affected by prediabetes, CDC has several efforts to increase the availability of the National DPP LCP including Cooperative Agreements such as “Scaling the National Diabetes Prevention Program in Underserved Areas” (DP17-1705). We assessed the presence of publicly available in-person LCP classes, as of March 1, 2017, by diabetes incidence and socioeconomic status at the county level, because higher diabetes incidence and lower socioeconomic status are correlated (3) and may be useful in targeting type 2 diabetes prevention efforts. Organizations wanting to expand the availability of the LCP may use these maps to determine counties most in need of new programs. |
Changes in diagnosed diabetes, obesity, and physical inactivity prevalence in US counties, 2004-2012
Geiss LS , Kirtland K , Lin J , Shrestha S , Thompson T , Albright A , Gregg EW . PLoS One 2017 12 (3) e0173428 Recent studies suggest that prevalence of diagnosed diabetes in the United States reached a plateau or slowed around 2008, and that this change coincided with obesity plateaus and increases in physical activity. However, national estimates can obscure important variations in geographic subgroups. We examine whether a slowing or leveling off in diagnosed diabetes, obesity, and leisure time physical inactivity prevalence is also evident across the 3143 counties of the United States. We used publicly available county estimates of the age-adjusted prevalence of diagnosed diabetes, obesity, and leisure-time physical inactivity, which were generated by the Centers for Disease Control and Prevention (CDC). Using a Bayesian multilevel regression that included random effects by county and year and applied cubic splines to smooth these estimates over time, we estimated the average annual percentage point change (APPC) from 2004 to 2008 and from 2008 to 2012 for diabetes, obesity, and physical inactivity prevalence in each county. Compared to 2004-2008, the median APPCs for diabetes, obesity, and physical inactivity were lower in 2008-2012 (diabetes APPC difference = 0.16, 95%CI 0.14, 0.18; obesity APPC difference = 0.65, 95%CI 0.59, 0.70; physical inactivity APPC difference = 0.43, 95%CI 0.37, 0.48). APPCs and APPC differences between time periods varied among counties and U.S. regions. Despite improvements, levels of these risk factors remained high with most counties merely slowing rather than reversing, which suggests that all counties would likely benefit from reductions in these risk factors. The diversity of trajectories in the prevalence of these risk factors across counties underscores the continued need to identify high risk areas and populations for preventive interventions. Awareness of how these factors are changing might assist local policy makers in targeting and tracking the impact of efforts to reduce diabetes, obesity and physical inactivity. |
Changes in disparity in county-level diagnosed diabetes prevalence and incidence in the United States, between 2004 and 2012
Shrestha SS , Thompson TJ , Kirtland KA , Gregg EW , Beckles GL , Luman ET , Barker LE , Geiss LS . PLoS One 2016 11 (8) e0159876 BACKGROUND: In recent decades, the United States experienced increasing prevalence and incidence of diabetes, accompanied by large disparities in county-level diabetes prevalence and incidence. However, whether these disparities are widening, narrowing, or staying the same has not been studied. We examined changes in disparity among U.S. counties in diagnosed diabetes prevalence and incidence between 2004 and 2012. METHODS: We used 2004 and 2012 county-level diabetes (type 1 and type 2) prevalence and incidence data, along with demographic, socio-economic, and risk factor data from various sources. To determine whether disparities widened or narrowed over the time period, we used a regression-based beta-convergence approach, accounting for spatial autocorrelation. We calculated diabetes prevalence/incidence percentage point (ppt) changes between 2004 and 2012 and modeled these changes as a function of baseline diabetes prevalence/incidence in 2004. Covariates included county-level demographic and, socio-economic data, and known type 2 diabetes risk factors (obesity and leisure-time physical inactivity). RESULTS: For each county-level ppt increase in diabetes prevalence in 2004 there was an annual average increase of 0.02 ppt (p<0.001) in diabetes prevalence between 2004 and 2012, indicating a widening of disparities. However, after accounting for covariates, diabetes prevalence decreased by an annual average of 0.04 ppt (p<0.001). In contrast, changes in diabetes incidence decreased by an average of 0.04 ppt (unadjusted) and 0.09 ppt (adjusted) for each ppt increase in diabetes incidence in 2004, indicating a narrowing of county-level disparities. CONCLUSIONS: County-level disparities in diagnosed diabetes prevalence in the United States widened between 2004 and 2012, while disparities in incidence narrowed. Accounting for demographic and, socio-economic characteristics and risk factors for type 2 diabetes narrowed the disparities, suggesting that these factors are strongly associated with changes in disparities. Public health interventions that target modifiable risk factors, such as obesity and physical inactivity, in high burden counties might further reduce disparities in incidence and, over time, in prevalence. |
Diabetes among Asians and Native Hawaiians or other Pacific Islanders - United States, 2011-2014
Kirtland KA , Cho P , Geiss LS . MMWR Morb Mortal Wkly Rep 2015 64 (45) 1261-6 Asians and Native Hawaiians or other Pacific Islanders (NHPIs) are fast-growing U.S. minority populations*(,dagger) at high risk for type 2 diabetes (1-4). Although national studies have described diabetes prevalence, incidence, and risk factors among Asians (2-5) and NHPIs (2,5) compared with non-Hispanic whites, little is known about state-level diabetes prevalence among these two racial groups, or about how they differ from one another with respect to diabetes risk factors. To examine state-level prevalence of self-reported, physician-diagnosed (diagnosed) diabetes and risk factors among Asians and NHPIs aged ≥18 years, CDC analyzed data from the 2011-2014 Behavioral Risk Factor Surveillance System (BRFSS). Among five states and Guam with sufficient data about NHPIs for analysis, the age-adjusted diabetes prevalence estimate for NHPIs ranged from 13.4% (New York) to 19.1% (California). Among 32 states, the District of Columbia (DC), and Guam that had sufficient data about Asians for analysis, diabetes prevalence estimates for Asians ranged from 4.9% (Arizona) to 15.3% (New York). In the five states and Guam with sufficient NHPI data, NHPIs had a higher age-adjusted prevalence of diabetes than did Asians, and a higher proportion of NHPIs were overweight or obese and had less than a high school education compared with Asians. Effective interventions and policies might reduce the prevalence of diabetes in these growing, high-risk minority populations. |
Geographic disparity of severe vision loss - United States, 2009-2013
Kirtland KA , Saaddine JB , Geiss LS , Thompson TJ , Cotch MF , Lee PP . MMWR Morb Mortal Wkly Rep 2015 64 (19) 513-7 Vision loss and blindness are among the top 10 disabilities in the United States, causing substantial social, economic, and psychological effects, including increased morbidity, increased mortality, and decreased quality of life. There are disparities in vision loss based on age, sex, race/ethnicity, socioeconomic status, and geographic location. Current surveillance activities using national and state surveys have characterized vision loss at national and state levels. However, there are limited data and research at local levels, where interventions and policy decisions to reduce the burden of vision loss and eliminate disparities are often developed and implemented. CDC analyzed data from the American Community Survey (ACS) to estimate county-level prevalence of severe vision loss (SVL) (being blind or having serious difficulty seeing even when wearing glasses) in the United States and to describe its geographic pattern and its association with poverty level. Distinct geographic patterns of SVL prevalence were found in the United States; 77.3% of counties in the top SVL prevalence quartile (≥4.2%) were located in the South. SVL was significantly correlated with poverty (r = 0.5); 437 counties were in the top quartiles for both SVL and poverty, and 83.1% of those counties were located in southern states. A better understanding of the underlying barriers and facilitators of access and use of eye care services at the local level is needed to enable the development of more effective interventions and policies, and to help planners and practitioners serve the growing population with and at risk for vision loss more efficiently. |
Diabetes Interactive Atlas
Kirtland KA , Burrows NR , Geiss LS . Prev Chronic Dis 2014 11 E17 The Diabetes Interactive Atlas is a recently released Web-based collection of maps that allows users to view geographic patterns and examine trends in diabetes and its risk factors over time across the United States and within states. The atlas provides maps, tables, graphs, and motion charts that depict national, state, and county data. Large amounts of data can be viewed in various ways simultaneously. In this article, we describe the design and technical issues for developing the atlas and provide an overview of the atlas' maps and graphs. The Diabetes Interactive Atlas improves visualization of geographic patterns, highlights observation of trends, and demonstrates the concomitant geographic and temporal growth of diabetes and obesity. |
State-specific synthetic estimates of health status groups among inactive older adults with self-reported diabetes, 2000-2009
Kirtland KA , Zack MM , Caspersen CJ . Prev Chronic Dis 2012 9 E89 INTRODUCTION: Physical activity helps diabetic older adults who have physical impairments or comorbid conditions to control their disease. To enable state planners to select physical activity programs for these adults, we calculated synthetic state-specific estimates of inactive older adults with diabetes, categorized by defined health status groups. METHODS: Using data from the 2000 through 2009 National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS), we calculated synthetic state-specific estimates of inactive adults with diabetes who were aged 50 years or older for 5 mutually exclusive health status groups: 1) homebound, 2) frail (functional difficulty in walking one-fourth mile, climbing 10 steps, standing for 2 hours, and stooping, bending, and kneeling), 3) functionally impaired (difficulty in 1 to 3 of these functions), 4) having 1 or more comorbid conditions (with no functional impairments), and 5) healthy (no impairments or comorbid conditions). We combined NHIS regional proportions for the health status groups of inactive, older diabetic adults with BRFSS data of older diabetic adults to estimate state-specific proportions and totals. RESULTS: State-specific estimates of health status groups among all older adults ranged from 2.2% to 3.0% for homebound, 5.8% to 8.8% for frail, 20.1% to 26.1% for impaired, 34.9% to 43.7% for having comorbid conditions, and 4.0% to 6.9% for healthy; the remainder were older active diabetic adults. Except for the homebound, the percentages in these health status groups varied significantly by region and state. CONCLUSION: These state-specific estimates correspond to existing physical activity programs to match certain health status characteristics of groups and may be useful to program planners to meet the needs of inactive, older diabetic adults. |
Geographic distribution of diagnosed diabetes in the U.S.: a diabetes belt
Barker LE , Kirtland KA , Gregg EW , Geiss LS , Thompson TJ . Am J Prev Med 2011 40 (4) 434-9 BACKGROUND: The American "stroke belt" has contributed to the study of stroke. However, U.S. geographic patterns of diabetes have not been as specifically characterized. PURPOSE: This study identifies a geographically coherent region of the U.S. where the prevalence of diagnosed diabetes is especially high, called the "diabetes belt." METHODS: In 2010, data from the 2007 and 2008 Behavioral Risk Factor Surveillance System were combined with county-level diagnosed diabetes prevalence estimates. Counties in close proximity with an estimated prevalence of diagnosed diabetes ≥11.0% were considered to define the diabetes belt. Prevalence of risk factors in the diabetes belt was compared to that in the rest of the U.S. The fraction of the excess risk associated with living in the diabetes belt associated with selected risk factors, both modifiable (sedentary lifestyle, obesity) and nonmodifiable (age, gender, race/ethnicity, education), was calculated. RESULTS: A diabetes belt consisting of 644 counties in 15 mostly southern states was identified. People in the diabetes belt were more likely to be non-Hispanic African-American, lead a sedentary lifestyle, and be obese than in the rest of the U.S. Thirty percent of the excess risk was associated with modifiable risk factors, and 37% with nonmodifiable factors. CONCLUSIONS: Nearly one third of the difference in diabetes prevalence between the diabetes belt and the rest of the U.S. is associated with sedentary lifestyle and obesity. Culturally appropriate interventions aimed at decreasing obesity and sedentary lifestyle in counties within the diabetes belt should be considered. |
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