Publications by authors named "Jennifer D Parker"

63 Publications

Multiple imputation to account for linkage ineligibility in the NHANES-CMS Medicaid linked data: General use versus subject specific imputation models.

Stat J IAOS 2019 Aug;35(3):443-456

Division of Research and Methodology, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD, USA.

Data from the National Health and Nutrition Examination Survey (NHANES) have been linked to the Center for Medicare and Medicaid Services' Medicaid Enrollment and Claims Files. As not all survey participants provide sufficient information to be eligible for record linkage, linked data often includes fewer records than the original survey data. This project presents an application of multiple imputation (MI) for handling missing Medicaid/CHIP status due to linkage refusals in linked NHANES-Medicaid data using the linked 1999-2004 NHANES data. By examining multiple outcomes and subgroups among children, the analyses compare the results from a multi-purpose dataset produced from a single MI model to that of individualized MI models. Outcomes examined here include obesity, untreated dental caries, attention deficit hyperactivity disorder (ADHD), and exposure to second hand smoke.
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http://dx.doi.org/10.3233/sji-180470DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437981PMC
August 2019

National Center for Health Statistics Data Presentation Standards for Proportions.

Vital Health Stat 2 2017 Aug(175):1-22

The National Center for Health Statistics (NCHS) disseminates information on a broad range of health topics through diverse publications. These publications must rely on clear and transparent presentation standards that can be broadly and efficiently applied. Standards are particularly important for large, cross-cutting reports where estimates cannot be individually evaluated and indicators of precision cannot be included alongside the estimates. This report describes the NCHS Data Presentation Standards for Proportions. The multistep NCHS Data Presentation Standards for Proportions are based on a minimum denominator sample size and on the absolute and relative widths of a confidence interval calculated using the Clopper-Pearson method. Proportions (usually multiplied by 100 and expressed as percentages) are the most commonly reported estimates in NCHS reports.
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August 2017

Accounting for study participants who are ineligible for linkage: a multiple imputation approach to analyzing the linked National Health and Nutrition Examination Survey and Centers for Medicare and Medicaid Services' Medicaid data.

Health Serv Outcomes Res Methodol 2018 Aug;19(2-3):87-105

Division of Research and Methodology, National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Mailstop P-08, Hyattsville, MD 20782-2064, USA.

Data from the National Health and Nutrition Examination Survey have been linked to the Center for Medicare and Medicaid Services' Medicaid Enrollment and Claims Files for the survey years 1999-2004. The linked data are produced by the National Center for Health Statistics' (NCHS) Data Linkage Program and are available in the NCHS Research Data Center. This project compares the usefulness of multiple imputation to account for data linkage ineligibility and other survey nonresponse with currently recommended weight adjustment procedures. Estimated differences in environmental smoke exposure across Medicaid/Children's Health Insurance Program (CHIP) enrollment status among children ages 3-15 years are examined as a motivating example. Comparisons are drawn across the three different estimates: one that uses MI to impute the administrative Medicaid/CHIP status of those who are ineligible for linkage, a second that uses the linked data restricted to linkage eligible participants with a basic weight adjustment, and a third that uses self-reported Medicaid/CHIP status from the survey data. The results indicate that estimates from the multiple imputation analysis were comparable to those found when using weight adjustment procedures and had the added benefit of incorporating all survey participants (linkage eligible and linkage ineligible) into the analysis. We conclude that both multiple imputation and weight adjustment procedures can effectively account for survey participants who are ineligible for linkage.
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http://dx.doi.org/10.1007/s10742-018-0186-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437992PMC
August 2018

National Health and Nutrition Examination Survey: Estimation Procedures, 2011-2014.

Vital Health Stat 2 2018 Jan(177):1-26

This report describes the methods used to create NHANES 2011-2014 sample weights and variance units for the public-use data files, including sample weights for selected subsamples, such as the fasting subsample. The impacts of sample design changes on estimation for NHANES 2011-2014 and the addition of the NHANES National Youth Fitness Survey (NNYFS) 2012 are described. Approaches that data users can employ to modify sample weights when combining survey cycles or when combining subsamples are also included.
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January 2018

Use of the National Health Interview Survey Linked to Medicaid Analytic eXtract Data to Identify Children With Medicaid-covered Births.

Natl Health Stat Report 2018 04(109):1-11

Objective-This report illustrates the use of National Health Interview Survey (NHIS) data linked to Medicaid Analytic eXtract (MAX) data to identify children whose births were covered by Medicaid, as indicated in MAX data, among those participating in NHIS in early childhood, and briefly describes their selected health characteristics.
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April 2018

Linkage of 1999-2012 National Health Interview Survey and National Health and Nutrition Examination Survey Data to U.S. Department of Housing and Urban Development Administrative Records.

Vital Health Stat 1 2017 10(60):1-40

Objectives This report presents the development, plan, and operation of the 2011-2012 National Survey of Children's Health, a module of the State and Local Area Integrated Telephone Survey, conducted by the National Center for Health Statistics. Funding was provided by the Maternal and Child Health Bureau, Health Resources and Services Administration. The survey was designed to produce national and state prevalence estimates of the physical and emotional health of children aged 0-17 years, as well as factors that may relate to child well-being including medical homes, family interactions, parental health, school and after-school experiences, and neighborhood characteristics.
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October 2017

Particulate Matter Air Pollution Exposure and Heart Disease Mortality Risks by Race and Ethnicity in the United States: 1997 to 2009 National Health Interview Survey With Mortality Follow-Up Through 2011.

Circulation 2018 04 13;137(16):1688-1697. Epub 2017 Dec 13.

National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA (A.V.).

Background: Most US studies of mortality and air pollution have been conducted on largely non-Hispanic white study populations. However, many health and mortality outcomes differ by race and ethnicity, and non-Hispanic white persons experience lower air pollution exposure than those who are non-Hispanic black or Hispanic. This study examines whether associations between air pollution and heart disease mortality differ by race/ethnicity.

Methods: We used data from the 1997 to 2009 National Health Interview Survey linked to mortality records through December 2011 and annual estimates of fine particulate matter (PM) by census tract. Proportional hazards models were used to estimate hazard ratios and 95% confidence intervals between PM (per 10 µg/m) and heart disease mortality using the full sample and the sample adults, which have information on additional health variables. Interaction terms were used to examine differences in the PM-mortality association by race/ethnicity.

Results: Overall, 65 936 of the full sample died during follow-up, and 22 152 died from heart disease. After adjustment for several factors, we found a significant positive association between PM and heart disease mortality (hazard ratio, 1.16; 95% confidence interval, 1.08-1.25). This association was similar in sample adults with adjustment for smoking and body mass index (hazard ratio, 1.18; 95% confidence interval, 1.06-1.31). Interaction terms for non-Hispanic black and Hispanic groups compared with the non-Hispanic white group were not statistically significant.

Conclusions: Using a nationally representative sample, the association between PM and heart disease mortality was elevated and similar to previous estimates. Associations for non-Hispanic black and Hispanic adults were not statistically significantly different from those for non-Hispanic white adults.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.117.029376DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908251PMC
April 2018

National Health and Nutrition Examination Survey: California and Los Angeles County, Estimation Methods and Analytic Considerations, 1999-2006 and 2007-2014.

Vital Health Stat 2 2017 May(173):1-26

Westsat.

Background California is the most populated state and Los Angeles County is the most populated county in the United States. National Health and Nutrition Examination Survey (NHANES) sample weights and variance units were developed for these places to obtain subnational estimates. Objective This report describes the California and Los Angeles County NHANES 1999-2006 and 2007-2014 samples, including the creation of the sample weights and variance units and descriptions of the resulting data files. Some analytic guidelines are provided. Results Eight years of NHANES data were combined for each data file to provide an adequate sample size and reduce disclosure risks. Because Los Angeles County has been a self-representing primary sampling unit, sample weights for Los Angeles County were relatively straightforward. However, a modelbased approach was used to create sample weights for California. The relatively large proportion of Mexican- American and other Hispanic persons in California, coupled with the different NHANES 1999-2014 sample design requirements for oversampling these groups within the small number of NHANES locations selected each cycle, led to a relatively large size of these groups in the California and Los Angeles County NHANES files. For example, 1,137 and 374 of the 3,353 Mexican-Americans persons in NHANES 2007-2014 were in the California and Los Angeles County samples, respectively. Conclusion The California and Los Angeles County NHANES 1999-2006 and 2007-2014 samples are available in the National Center for Health Statistics Research Data Center.
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May 2017

Racial and Ethnic Differences in a Linkage with the National Death Index.

Ethn Dis 2017 20;27(2):77-84. Epub 2017 Apr 20.

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland, United States.

Objectives: Differences in the availability of a Social Security Number (SSN) by race/ethnicity could affect the ability to link with death certificate data in passive follow-up studies and possibly bias mortality disparities reported with linked data. Using 1989-2009 National Health Interview Survey (NHIS) data linked with the National Death Index (NDI) through 2011, we compared the availability of a SSN by race/ethnicity, estimated the percent of links likely missed due to lack of SSNs, and assessed if these estimated missed links affect race/ethnicity disparities reported in the NHIS-linked mortality data.

Methods: We used preventive fraction methods based on race/ethnicity-specific Cox proportional hazards models of the relationship between availability of SSN and mortality based on observed links, adjusted for survey year, sex, age, respondent-rated health, education, and US nativity.

Results: Availability of a SSN and observed percent linked were significantly lower for Hispanic and Asian/Pacific Islander (PI) participants compared with White non-Hispanic participants. We estimated that more than 18% of expected links were missed due to lack of SSNs among Hispanic and Asian/PI participants compared with about 10% among White non-Hispanic participants. However, correcting the observed links for expected missed links appeared to only have a modest impact on mortality disparities by race/ethnicity.

Conclusions: Researchers conducting analyses of mortality disparities using the NDI or other linked death records, need to be cognizant of the potential for differential linkage to contribute to their results.
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http://dx.doi.org/10.18865/ed.27.2.77DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398181PMC
July 2019

The relationship between linkage refusal and selected health conditions of survey respondents.

Surv Pract 2016 Dec 31;9(5). Epub 2016 Aug 31.

National Center for Health Statistics.

To maximize limited resources and reduce respondent burden, there is an increased interest in linking population health surveys with other sources of data, such as administrative records. Health differences between adults who consent to and refuse linkage could bias study results with linked data. National Health Interview Survey (NHIS) data are routinely linked to administrative records from the Social Security Administration and the Centers for Medicare and Medicaid Services. Using the NHIS 2010-2013, we examined the association between selected health conditions and respondents' linkage refusal. Linkage refusal was significantly lower for adults with serious psychological distress, chronic obstructive pulmonary disease, diabetes, heart disease, stroke, hypertension, and cancer compared to those without these conditions. Linkage refusal decreased as the number of conditions increased and health status decreased. Our finding that linkage consent was associated with respondents' health characteristics suggests that researchers should try to address potential linkage bias in their analyses.
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http://dx.doi.org/10.29115/SP-2016-0028DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444367PMC
December 2016

Exposure to Extreme Heat Events Is Associated with Increased Hay Fever Prevalence among Nationally Representative Sample of US Adults: 1997-2013.

J Allergy Clin Immunol Pract 2017 Mar - Apr;5(2):435-441.e2. Epub 2016 Nov 8.

Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland, College Park, Md. Electronic address:

Background: Warmer temperature can alter seasonality of pollen as well as pollen concentration, and may impact allergic diseases such as hay fever. Recent studies suggest that extreme heat events will likely increase in frequency, intensity, and duration in coming decades in response to changing climate.

Objective: The overall objective of this study was to investigate if extreme heat events are associated with hay fever.

Methods: We linked National Health Interview Survey (NHIS) data from 1997 to 2013 (n = 505,386 respondents) with extreme heat event data, defined as days when daily maximum temperature (TMAX) exceeded the 95th percentile values of TMAX for a 30-year reference period (1960-1989). We used logistic regression to investigate the associations between exposure to annual and seasonal extreme heat events and adult hay fever prevalence among the NHIS respondents.

Results: During 1997-2013, hay fever prevalence among adults 18 years and older was 8.43%. Age, race/ethnicity, poverty status, education, and sex were significantly associated with hay fever status. We observed that adults in the highest quartile of exposure to extreme heat events had a 7% increased odds of hay fever compared with those in the lowest quartile of exposure (odds ratios: 1.07, 95% confidence interval: 1.02-1.11). This relationship was more pronounced for extreme heat events that occurred during spring season, with evidence of an exposure-response relationship (P < .01).

Conclusions: Our data suggest that exposure to extreme heat events is associated with increased prevalence of hay fever among US adults.
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http://dx.doi.org/10.1016/j.jaip.2016.09.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346329PMC
November 2017

MULTIPLE IMPUTATION FOR MISSINGNESS DUE TO NONLINKAGE AND PROGRAM CHARACTERISTICS: A CASE STUDY OF THE NATIONAL HEALTH INTERVIEW SURVEY LINKED TO MEDICARE CLAIMS.

J Surv Stat Methodol 2016 Sep 21;4(3):316-338. Epub 2016 May 21.

National Center for Health Statistics, Hyattsville, MD 20782, USA.

Record linkage is a valuable and efficient tool for connecting information from different data sources. The National Center for Health Statistics (NCHS) has linked its population-based health surveys with administrative data, including Medicare enrollment and claims records. However, the linked NCHS-Medicare files are subject to missing data; first, not all survey participants agree to record linkage, and second, Medicare claims data are only consistently available for beneficiaries enrolled in the Fee-for-Service (FFS) program, not in Medicare Advantage (MA) plans. In this research, we examine the usefulness of multiple imputation for handling missing data in linked National Health Interview Survey (NHIS)-Medicare files. The motivating example is a study of mammography status from 1999 to 2004 among women aged 65 years and older enrolled in the FFS program. In our example, mammography screening status and FFS/MA plan type are missing for NHIS survey participants who were not linkage eligible. Mammography status is also missing for linked participants in an MA plan. We explore three imputation approaches: (i) imputing screening status first, (ii) imputing FFS/MA plan type first, (iii) and imputing the two longitudinal processes simultaneously. We conduct simulation studies to evaluate these methods and compare them using the linked NHIS-Medicare files. The imputation procedures described in our paper would also be applicable to other public health-related research using linked data files with missing data issues arising from program characteristics (e.g., intermittent enrollment or data collection) reflected in administrative data and linkage eligibility by survey participants.
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http://dx.doi.org/10.1093/jssam/smw002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6444366PMC
September 2016

Characteristics of Medicare Advantage and Fee-for-Service Beneficiaries Upon Enrollment in Medicare at Age 65.

J Ambul Care Manage 2016 Jul-Sep;39(3):231-41

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland.

Previous research has found differences in characteristics of beneficiaries enrolled in Medicare fee-for-service versus Medicare Advantage (MA), but there has been limited research using more recent MA enrollment data. We used 1997-2005 National Health Interview Survey data linked to 2000-2009 Medicare enrollment data to compare characteristics of Medicare beneficiaries before their initial enrollment into Medicare fee-for-service or MA at age 65 and whether the characteristics of beneficiaries changed from 2006 to 2009 compared with 2000 to 2005. During this period of MA growth, the greatest increase in enrollment appears to have come from those with no chronic conditions and men.
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http://dx.doi.org/10.1097/JAC.0000000000000107DOI Listing
July 2017

Blood Lead and Other Metal Biomarkers as Risk Factors for Cardiovascular Disease Mortality.

Medicine (Baltimore) 2016 Jan;95(1):e2223

From the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Hyattsville, MD (YA, DJB, KMF, THIF, JDP); and Office of Policy, Environmental Protection Agency, Washington, DC, USA (DAA).

Analyses of the Third National Health and Nutrition Examination Survey (NHANES III) in 1988 to 1994 found an association of increasing blood lead levels < 10 μg/dL with a higher risk of cardiovascular disease (CVD) mortality. The potential need to correct blood lead for hematocrit/hemoglobin and adjust for biomarkers for other metals, for example, cadmium and iron, had not been addressed in the previous NHANES III-based studies on blood lead-CVD mortality association. We analyzed 1999 to 2010 NHANES data for 18,602 participants who had a blood lead measurement, were ≥ 40 years of age at the baseline examination and were followed for mortality through 2011. We calculated the relative risk for CVD mortality as a function of hemoglobin- or hematocrit-corrected log-transformed blood lead through Cox proportional hazard regression analysis with adjustment for serum iron, blood cadmium, serum C-reactive protein, serum calcium, smoking, alcohol intake, race/Hispanic origin, and sex. The adjusted relative risk for CVD mortality was 1.44 (95% confidence interval = 1.05, 1.98) per 10-fold increase in hematocrit-corrected blood lead with little evidence of nonlinearity. Similar results were obtained with hemoglobin-corrected blood lead. Not correcting blood lead for hematocrit/hemoglobin resulted in underestimation of the lead-CVD mortality association while not adjusting for iron status and blood cadmium resulted in overestimation of the lead-CVD mortality association. In a nationally representative sample of U.S. adults, log-transformed blood lead was linearly associated with increased CVD mortality. Correcting blood lead for hematocrit/hemoglobin and adjustments for some biomarkers affected the association.
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http://dx.doi.org/10.1097/MD.0000000000002223DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4706249PMC
January 2016

Linkage of NCHS Population Health Surveys to Administrative Records From Social Security Administration and Centers for Medicare Medicaid Services.

Vital Health Stat 1 2015 09(58):1-53

Federally sponsored health surveys are a critical source of information on public health in the United States. The National Center for Health Statistics (NCHS) is the nation's principal health statistics agency and is responsible for collecting accurate, relevant, and timely data. NCHS conducts several population-based national surveys as well as collecting vital statistics data, which are used by a broad range of users (researchers and policy makers, among others) to evaluate and profile the health of the American people. These national health surveys provide rich cross-sectional information on risk factors such as smoking, height and weight, health status, and socioeconomic circumstances, but information on longitudinal outcomes is often missing. Demand is increasing to incorporate information from additional sources in order to enhance the availability and quality of information on exposures and outcomes.
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September 2015

Characteristics of Children in Medicaid Managed Care and Medicaid Fee-for-service, 2003-2005.

Natl Health Stat Report 2015 Jun(80):1-15

Objectives: Medicaid claims have been used to characterize utilization patterns of child Medicaid beneficiaries. However, because states are increasingly adopting Medicaid managed care plans, analyses of children enrolled in Medicaid based only on claims for fee-for-service (FFS) programs may not apply to the general Medicaid population.

Methods: The 2003-2005 National Health Interview Survey and 2003-2005 Medicaid Analytic eXtract linked files were used to examine associations between sociodemographic, health, and geographic characteristics of children aged 0-17 years and enrollment in Medicaid FFS compared with a comprehensive managed care (CMC) program. Additional analyses of age-specific health outcomes were performed on a subset of children aged 6-17 years. Chi-square tests were used to assess associations, and 95% confidence intervals are provided for point prevalence estimates.

Results: Higher percentages of children in CMC compared with FFS were non-Hispanic white, lived in families with income less than 100% of the federal poverty level, had excellent or very good health, lived in the Northeast and West, and lived in large central metro areas. No significant differences were observed by sex, age, and asthma diagnoses between children enrolled in CMC and FFS. Among children aged 6-17 years, higher percentages of children enrolled in FFS compared with children in CMC were diagnosed with learning disabilities or developmental delays and attention deficit hyperactivity disorder. Researchers using data from children enrolled only in Medicaid FFS programs to describe children enrolled in Medicaid should understand differences between children in CMC and FFS. Generalization of study results from FFS claims may depend on the outcomes examined.
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June 2015

Serious Psychological Distress Among Adults: United States, 2009-2013.

NCHS Data Brief 2015 May(203):1-8

In every age group, women were more likely to have serious psychological distress than men. Among all adults, as income increased, the percentage with serious psychological distress decreased. Adults aged 18-64 with serious psychological distress were more likely to be uninsured (30.4%) than adults without serious psychological distress (20.5%). More than one-quarter of adults aged 65 and over with serious psychological distress (27.3%) had limitations in activities of daily living. Adults with serious psychological distress were more likely to have chronic obstructive pulmonary disease, heart disease, and diabetes than adults without serious psychological distress.
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May 2015

Linkage of 1986-2009 National Health Interview Survey with 1981-2010 Florida Cancer Data System.

Vital Health Stat 2 2014 Sep(167):1-16

Purdue University.

Background: National survey data linked with state cancer registry data has the potential to create a valuable tool for cancer prevention and control research. A pilot project-developed in a collaboration of the Centers for Disease Control and Prevention's National Center for Health Statistics (NCHS) and the Florida Cancer Data System (FCDS) at the University of Miami -links the records of the 1986-2009 National Health Interview Survey (NHIS) and the 1981-2010 FCDS. The project assesses the feasibility of performing a record linkage between NCHS survey data and a state-based cancer registry, as well as the value of the data produced. The linked NHIS-FCDS data allow researchers to follow NHIS survey participants longitudinally to examine factors associated with future cancer diagnosis, and to assess the characteristics and quality of life among cancer survivors.

Methods: This report provides a preliminary evaluation of the linked national and state cancer data and examines both analytic issues and complications presented by the linkage.

Conclusions: Residential mobility and the number of years of data linked in this project create some analytic challenges and limitations for the types of analyses that can be conducted. However, the linked data set offers the ability to conduct analyses not possible with either data set alone.
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September 2014

Deaths attributed to heat, cold, and other weather events in the United States, 2006-2010.

Natl Health Stat Report 2014 Jul(76):1-15

National Center for Health Statistics.

Objectives: This report examines heat-related mortality, cold-related mortality, and other weather-related mortality during 2006-2010 among subgroups of U.S. residents.

Methods: Weather-related death rates for demographic and area-based subgroups were computed using death certificate information. Adjusted odds ratios for weather-related deaths among subgroups were estimated using logistic regression.

Results And Conclusions: During 2006-2010, about 2,000 U.S. residents died each year from weather-related causes of death. About 31% of these deaths were attributed to exposure to excessive natural heat, heat stroke, sun stroke, or all; 63% were attributed to exposure to excessive natural cold, hypothermia, or both; and the remaining 6% were attributed to floods, storms, or lightning. Weather-related death rates varied by age, race and ethnicity, sex, and characteristics of decedent's county of residence (median income, region, and urbanization level). Adjustment for region and urbanization decreased the risk of heat-related mortality among Hispanic persons and increased the risk of cold-related mortality among non-Hispanic black persons, compared with non-Hispanic white persons. Adjustment also increased the risk of heat-related mortality and attenuated the risk of cold-related mortality for counties in the lower three income quartiles. The differentials in weather-related mortality observed among demographic subgroups during 2006-2010 in the United States were consistent with those observed in previous national studies. This study demonstrated that a better understanding of subpopulations at risk from weather-related mortality can be obtained by considering area-based variables (county median household income, region, and urbanization level) when examining weather-related mortality patterns.
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July 2014

Self-report of diabetes and claims-based identification of diabetes among Medicare beneficiaries.

Natl Health Stat Report 2013 Nov(69):1-14

Objective: This report compares self-reported diabetes in the National Health Interview Survey (NHIS) with diabetes identified using the Medicare Chronic Condition (CC) Summary file.

Background: NHIS records have been linked with Medicare data from the Centers for Medicare & Medicaid Services. The CC Summary file, one of several linked files derived from Medicare claims data, contains indicators for chronic conditions based on an established algorithm.

Methods: This analysis was limited to 2005 NHIS participants aged 65 and over whose records were linked to 2005 Medicare data. Linked NHIS participants had at least 1 month of fee-for-service Medicare coverage in 2005. Concordance between self-reported diabetes and the CC Summary indicator for diabetes is compared and described by demographics, socioeconomic status, health status indicators, and geographic characteristics.

Results: Of the Medicare beneficiaries in the 2005 NHIS, 20.0% self-reported diabetes and 27.8% had an indicator for diabetes in the CC Summary file. Of those who self-reported diabetes in NHIS, the percentage with a CC Summary indicator for diabetes was high (93.1%). Of those with a CC Summary indicator for diabetes, the percentage self-reporting diabetes was comparatively lower (67.0%). Statistically significant differences by subgroup existed in the percentage concordance between the two sources. Of those with self-reported diabetes, the percentage with a CC Summary indicator differed by sex and age. Of those with a CC Summary indicator for diabetes, the percentage with self-reported diabetes differed by age, self-rated health, number of self-reported conditions, and geographic location.

Conclusions: Among Medicare beneficiaries who self-reported diabetes in NHIS, a high concordance was observed with identification of diabetes in the CC Summary file. However, among Medicare beneficiaries with an indicator for diabetes in the CC Summary file, concordance with self-reported diabetes in NHIS is comparatively lower. Differences exist by subgroup.
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November 2013

Diabetes and colorectal cancer screening among men and women in the USA: National Health Interview Survey: 2008, 2010.

Cancer Causes Control 2014 May 23;25(5):553-60. Epub 2014 Feb 23.

National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD, 20782, USA,

Purpose: Adults with diabetes are at increased risk of being diagnosed with and dying from colorectal cancer, but it is unclear whether colorectal cancer screening (CRCS) use is lower in this population. Using the 2008 and 2010 National Health Interview Survey data, we examined whether guideline-concordant CRCS is lower among men and women with self-reported diabetes.

Methods: We calculated the weighted percentage of guideline-concordant CRCS and unadjusted and adjusted prevalence ratios (PR) comparing adults aged 51-75 years with diabetes (n = 6,514) to those without (n = 8,371). We also examined effect modification by age (51-64 and 65-75), race/ethnicity, and number of medical office visits (0-3, ≥ 4).

Results: The unadjusted prevalence of CRCS among men with diabetes was significantly higher than men without (63.3 vs. 58.0 %; PR = 1.09 95 % CI 1.03-1.16). In adjusted models, this relationship was evident among older [adjusted PR (aPR) = 1.13 95 % CI 1.06-1.21] but not younger men (aPR = 0.99 95 % CI 0.91-1.08; p for interaction term ≤ 0.01). There was no significant association between diabetes and CRCS among women overall (56.6 vs. 57.9 %; PR = 0.98 95 % CI 0.92-1.04) or by age group. Race/ethnicity and the number of medical visits did not significantly modify the association between diabetes and CRCS for men or women.

Conclusions: Men and women with self-reported diabetes were not less likely to be up to date with CRCS than those without diabetes. Older men with diabetes were more likely to be up to date with CRCS than those without diabetes.
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http://dx.doi.org/10.1007/s10552-014-0360-zDOI Listing
May 2014

A longitudinal view of child enrollment in Medicaid.

Pediatrics 2013 Oct 23;132(4):656-62. Epub 2013 Sep 23.

Medical Officer/Senior Service Fellow, National Center for Health Statistics, 3311 Toledo Rd, Room 6122, Hyattsville, MD 20782.

Background: Although national cross-sectional estimates of the percentage of children enrolled in Medicaid are available, the percentage of children enrolled in Medicaid over longer periods of time is unknown. Also, the percentage and characteristics of children who rely on Medicaid throughout childhood, rather than transiently, are unknown.

Methods: We performed a longitudinal examination of Medicaid coverage among children across a 5-year period. Children 0 to 13 years of age in the 2004 National Health Interview Survey file were linked to Medicaid Analytic eXtract files from 2004 to 2008. The percentage of children enrolled in Medicaid at any time during the 5-year observation period and the number of years during which children were enrolled in Medicaid were calculated. Duration of Medicaid enrollment was compared across sociodemographic characteristics by using χ(2) tests.

Results: Forty-one percent of all US children were enrolled in Medicaid at least some time during the 5-year period, compared with a single-year estimate of 32.8% in 2004 alone. Of enrolled children, 51.5% were enrolled during all 5 years. Children with lower parental education, with lower household income, of minority race or ethnicity, and in suboptimal health were more likely to be enrolled in Medicaid during all 5 years.

Conclusions: Longitudinal data reveal higher percentages of children with Medicaid insurance than shown by cross-sectional data. Half of children enrolled in Medicaid are enrolled during at least 5 consecutive years, and these children have higher risk sociodemographic profiles.
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http://dx.doi.org/10.1542/peds.2013-1544DOI Listing
October 2013

Identifying implausible gestational ages in preterm babies with Bayesian mixture models.

Stat Med 2013 May 4;32(12):2097-113. Epub 2012 Nov 4.

National Center for Health Statistics, Hyattsville, MD, 20782, USA.

Infant birth weight and gestational age are two important variables in obstetric research. The primary measure of gestational age used in US birth data is based on a mother's recall of her last menstrual period, which has been shown to introduce random or systematic errors. To mitigate some of those errors, Oja et al., Platt et al., and Tentoni et al. estimated the probabilities of gestational ages being misreported under the assumption that the distribution of infant birth weights for a true gestational age is approximately Gaussian. From this assumption, Oja et al. fitted a three-component mixture model, and Tentoni et al. and Platt et al. fitted two-component mixture models. We build on their methods and develop a Bayesian mixture model. We then extend our methods using reversible jump Markov chain Monte Carlo to incorporate the uncertainty in the number of components in the model. We conduct simulation studies and apply our methods to singleton births with reported gestational ages of 23-32 weeks using 2001-2008 US birth data. Results show that a three-component mixture model fits the birth data better for gestational ages reported as 25 weeks or less; and a two-component mixture model fits better for the higher gestational ages. Under the assumption that our Bayesian mixture models are appropriate for US birth data, our research provides useful statistical tools to identify records with implausible gestational ages, and the techniques can be used in part of a multiple-imputation procedure for missing and implausible gestational ages.
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http://dx.doi.org/10.1002/sim.5657DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426294PMC
May 2013

Health characteristics of Medicare traditional fee-for-service and Medicare Advantage enrollees: 1999-2004 National Health and Nutrition Examination Survey linked to 2007 Medicare data.

Natl Health Stat Report 2012 May(53):1-12

Division of Health and Nutrition Examination Surveys, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics, Hyattsville, MD 20782, USA.

Background: National Health and Nutrition Examination Survey (NHANES) records have been linked to health care use and expenditure information from Medicare records. Claims data are generally available only for traditional fee-for-service (FFS) enrollees and not for Medicare Advantage enrollees. Differences in health characteristics between Medicare Advantage and traditional FFS enrollees could affect conclusions from analyses of the linked files that are restricted to traditional FFS enrollees.

Methods: Data from the 1999-2004 NHANES linked to the 2007 Medicare enrollment data were analyzed. Using examination and interview data collected in NHANES, we compared health characteristics of Medicare beneficiaries aged 65 and over at the NHANES interview by their type of Medicare enrollment in 2007.

Results: We found that the overall percentage of Medicare beneficiaries who had hypertension at the time of the NHANES medical examination was lower for Medicare Advantage enrollees compared with traditional FFS enrollees; this was found for the non-Hispanic white population but not for other race and ethnicity groups. We found no statistically significant differences between Medicare Advantage and traditional FFS enrollees overall or within race and ethnicity groups for other health characteristics that were measured or reported at the time of the NHANES interview or medical examination in 1999-2004.

Conclusions: Despite finding no large differences in health characteristics by Medicare enrollment in this analysis, users of the National Center for Health Statistics Medicare linked files should consider potential differences in health characteristics between Medicare Advantage and traditional FFS enrollees that could influence results limited to traditional FFS beneficiaries only.
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May 2012

Linkage of the 1999-2008 National Health and Nutrition Examination Surveys to traffic indicators from the National Highway Planning Network.

Natl Health Stat Report 2012 Apr(45):1-16

U.S. Department of Health and Human Services, Centers For Disease Control and Prevention, Office of Analysis and Epidemiology, National Center for Health Statistics, Hyattsville, MD 20782, USA.

Objectives: Growing evidence has shown the harmful effects of traffic-related pollution on human health, including adverse respiratory, cardiovascular, and pregnancy outcomes. This report describes the linkage of data from the 1999-2008 National Health and Nutrition Examination Surveys (NHANES) and traffic indicators from the 2005 National Highway Planning Network.

Methods: The residential addresses of NHANES participants were used to assign the distance to the nearest road, the number of roads within concentric buffers of specific radii, and the average annual daily traffic. Summaries of these traffic indicators by participant characteristics, including urbanization of their county of residence, race and ethnicity, poverty status, and health status, were tabulated.

Results: Using the traffic indicators, these data show differences in traffic exposure by several participant characteristics including poverty status. Further, reporting of fair or poor health was more common among NHANES respondents nearer to, compared with farther from, roads; this relationship was observed overall and for subgroups defined by urban county of residence, poverty status, and self-reported cigarette smoking.

Conclusions: These data may be a resource for understanding relationships between traffic exposure and adverse health, and for identifying subgroups that may be at increased risk. The NHANES-traffic data are restricted use and available to data users in the Research Data Center at the Centers for Disease Control and Prevention's National Center for Health Statistics.
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April 2012

Exposures to fine particulate air pollution and respiratory outcomes in adults using two national datasets: a cross-sectional study.

Environ Health 2012 Apr 10;11:25. Epub 2012 Apr 10.

Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Background: Relationships between chronic exposures to air pollution and respiratory health outcomes have yet to be clearly articulated for adults. Recent data from nationally representative surveys suggest increasing disparity by race/ethnicity regarding asthma-related morbidity and mortality. The objectives of this study are to evaluate the relationship between annual average ambient fine particulate matter (PM2.5) concentrations and respiratory outcomes for adults using modeled air pollution and health outcome data and to examine PM2.5 sensitivity across race/ethnicity.

Methods: Respondents from the 2002-2005 National Health Interview Survey (NHIS) were linked to annual kriged PM2.5 data from the USEPA AirData system. Logistic regression was employed to investigate increases in ambient PM2.5 concentrations and self-reported prevalence of respiratory outcomes including asthma, sinusitis and chronic bronchitis. Models included health, behavioral, demographic and resource-related covariates. Stratified analyses were conducted by race/ethnicity.

Results: Of nearly 110,000 adult respondents, approximately 8,000 and 4,000 reported current asthma and recent attacks, respectively. Overall, odds ratios (OR) for current asthma (0.97 (95% Confidence Interval: 0.87-1.07)) and recent attacks (0.90 (0.78-1.03)) did not suggest an association with a 10 μg/m3 increase in PM2.5. Stratified analyses revealed significant associations for non-Hispanic blacks [OR = 1.73 (1.17-2.56) for current asthma and OR = 1.76 (1.07-2.91) for recent attacks] but not for Hispanics and non-Hispanic whites. Significant associations were observed overall (1.18 (1.08-1.30)) and in non-Hispanic whites (1.31 (1.18-1.46)) for sinusitis, but not for chronic bronchitis.

Conclusions: Non-Hispanic blacks may be at increased sensitivity of asthma outcomes from PM2.5 exposure. Increased chronic PM2.5 exposures in adults may contribute to population sinusitis burdens.
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http://dx.doi.org/10.1186/1476-069X-11-25DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3361500PMC
April 2012

Prepregnancy body mass index and gestational weight gain in relation to child body mass index among siblings.

Am J Epidemiol 2011 Nov 7;174(10):1159-65. Epub 2011 Oct 7.

National Center for Health Statistics, Centers for Disease Control and Prevention, 3311 Toledo Road, Hyattsville, MD 20782, USA.

There is increasing evidence that in utero effects of excessive gestational weight gain may result in increased weight in children; however, studies have not controlled for shared genetic or environmental factors between mothers and children. Using 2,758 family groups from the Collaborative Perinatal Project, the authors examined the association of maternal prepregnancy body mass index (BMI) and gestational weight gain on child BMI at age 4 years using both conventional generalized estimating equations and fixed-effects models that account for shared familial factors. With generalized estimating equations, prepregnancy BMI and gestational weight gain had similar associations with the child BMI z score (β = 0.09 units, 95% confidence interval (CI): 0.08, 0.11; and β = 0.07 units, 95% CI: 0.04, 0.11, respectively. However, fixed effects resulted in null associations for both prepregnancy BMI (β = 0.03 units, 95% CI: -0.01, 0.07) and gestational weight gain (β = 0.03 units, 95% CI: -0.02, 0.08) with child BMI z score at age 4 years. The positive association between gestational weight gain and child BMI at age 4 years may be explained by shared family characteristics (e.g., genetic, behavioral, and environmental factors) rather than in utero programming. Future studies should continue to evaluate the relative roles of important familial and environmental factors that may influence BMI and obesity in children.
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http://dx.doi.org/10.1093/aje/kwr250DOI Listing
November 2011

The International Collaboration on Air Pollution and Pregnancy Outcomes: initial results.

Environ Health Perspect 2011 Jul 9;119(7):1023-8. Epub 2011 Feb 9.

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, Maryland 20782, USA.

Background: The findings of prior studies of air pollution effects on adverse birth outcomes are difficult to synthesize because of differences in study design.

Objectives: The International Collaboration on Air Pollution and Pregnancy Outcomes was formed to understand how differences in research methods contribute to variations in findings. We initiated a feasibility study to a) assess the ability of geographically diverse research groups to analyze their data sets using a common protocol and b) perform location-specific analyses of air pollution effects on birth weight using a standardized statistical approach.

Methods: Fourteen research groups from nine countries participated. We developed a protocol to estimate odds ratios (ORs) for the association between particulate matter ≤ 10 μm in aerodynamic diameter (PM₁₀) and low birth weight (LBW) among term births, adjusted first for socioeconomic status (SES) and second for additional location-specific variables.

Results: Among locations with data for the PM₁₀ analysis, ORs estimating the relative risk of term LBW associated with a 10-μg/m³ increase in average PM₁₀ concentration during pregnancy, adjusted for SES, ranged from 0.63 [95% confidence interval (CI), 0.30-1.35] for the Netherlands to 1.15 (95% CI, 0.61-2.18) for Vancouver, with six research groups reporting statistically significant adverse associations. We found evidence of statistically significant heterogeneity in estimated effects among locations.

Conclusions: Variability in PM₁₀-LBW relationships among study locations remained despite use of a common statistical approach. A more detailed meta-analysis and use of more complex protocols for future analysis may uncover reasons for heterogeneity across locations. However, our findings confirm the potential for a diverse group of researchers to analyze their data in a standardized way to improve understanding of air pollution effects on birth outcomes.
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http://dx.doi.org/10.1289/ehp.1002725DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3222970PMC
July 2011

Blood lead and mercury levels in pregnant women in the United States, 2003-2008.

NCHS Data Brief 2010 Dec(52):1-8

Centers for Disease Control and Prevention, National Center for Health Statistics, Office of Analysis and Epidemiology, Hyattsville, Maryland 20782, USA.

Chemical exposure during pregnancy is potentially harmful to the developing fetus, as the placenta cannot protect against heavy metals such as lead and mercury. Cord blood mercury levels have been associated with childhood cognitive function. High levels of lead exposure during pregnancy have been associated with adverse birth outcomes and, in some studies, with lower cognitive function test scores in childhood; relatively low lead levels have recently been associated with a small risk of decreased birthweight. While intervention for pregnant women with blood lead levels greater than or equal to 5 μg/dL has been recommended, no comparable recommendation for blood mercury in pregnant women has been established.This report presents geometric mean lead and mercury blood levels of pregnant women in the United States based on using the 2003-2008 National Health and Nutrition Examination Surveys (NHANES). Throughout this report, the term mean refers to the geometric mean.
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December 2010

The use of covariates to identify records with implausible gestational ages using the birthweight distribution.

Paediatr Perinat Epidemiol 2010 Sep;24(5):424-32

Office of Analysis and Epidemiology, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD 20782-2003, USA.

The objective of this study was to evaluate the usefulness of covariates in identifying birth records with implausible values of gestational age. Birthweight distributions for births with early reported gestational ages are markedly bimodal, suggesting a mixture of two distributions. Most births form a normal-shaped left-hand (primary) distribution and a smaller number form the right-hand (secondary) distribution. The births in the secondary distribution are thought to have gestational age mistakenly reported. Prior work has found that births in the secondary distribution are at higher risk of poor outcomes than those in the primary distribution. Using 2002 US Natality data for gestational ages 26-35 weeks, we fit normal mixture models to birthweight with and without covariates (maternal race, education, parity, age, region of the country, prenatal care initiation) by reported gestational age. Additional models were stratified by infant sex. This approach allowed for the relationship between the covariates and birthweight to differ between the components. Mixture models fit reasonably well for reported gestational ages <33 weeks, but not for later weeks. Counter to the hypothesis, results were similar for models with and without covariates or stratification or both, although stratified models without covariates predicted slightly more girls and slightly fewer boys in the secondary distribution than did the corresponding unstratified models. For reported gestational ages <33 weeks, predictions from the four sets of models were highly correlated and predictions were similar for subgroups defined by the clinical estimates of gestational age and other covariates. For births with reported gestational ages of 29 or more weeks, the proportion in the secondary distribution exceeded 30%, although this varied by maternal characteristics. The use of covariates and stratification complicated model fitting without materially improving identification of implausible gestational age values, supporting inferences from prior studies using data 'cleaned' without consideration of maternal or infant characteristics.
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http://dx.doi.org/10.1111/j.1365-3016.2010.01138.xDOI Listing
September 2010