Publications by authors named "Lauren M Rossen"

57 Publications

Rural-Urban Residence and Maternal Hepatitis C Infection, U.S.: 2010-2018.

Am J Prev Med 2021 Feb 24. Epub 2021 Feb 24.

Maine Rural Health Research Center, Muskie School of Public Service, University of Southern Maine, Portland, Maine.

Introduction: The prevalence of hepatitis C virus infection among women delivering live births in the U.S. may be higher in rural areas where county-level estimates may be unreliable. The aim of this study is to model county-level maternal hepatitis C virus infection among deliveries in the U.S.

Methods: In 2020, U.S. natality files (2010-2018) with county-level maternal residence information were used from states that had adopted the 2003 revised U.S. birth certificate, which included a field for hepatitis C virus infection present during pregnancy. Hierarchical Bayesian spatial models with spatiotemporal random effects were applied to produce stable annual county-level estimates of maternal hepatitis C virus infection for years when all states had adopted the revised birth certificate (2016-2018). Models included a 6-Level Urban-Rural County Classification Scheme along with the birth year and county-specific covariates to improve posterior predictions.

Results: Among approximately 32 million live births, the overall prevalence of maternal hepatitis C virus infection was 3.5 per 1,000 births (increased from 2.0 in 2010 to 5.0 in 2018). During 2016-2018, posterior predicted median county-level maternal hepatitis C virus infection rates showed that nonurban counties had 3.5-3.8 times higher rates of hepatitis C virus than large central metropolitan counties. The counties in the top 10th percentile for maternal hepatitis C virus rates in 2018 were generally located in Appalachia, in Northern New England, along the northern border in the Upper Midwest, and in New Mexico.

Conclusions: Further implementation of community-level interventions that are effective in reducing maternal hepatitis C virus infection and its subsequent morbidity may help to reduce geographic and rural disparities.
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http://dx.doi.org/10.1016/j.amepre.2020.12.020DOI Listing
February 2021

Race, Ethnicity, and Age Trends in Persons Who Died from COVID-19 - United States, May-August 2020.

MMWR Morb Mortal Wkly Rep 2020 Oct 23;69(42):1517-1521. Epub 2020 Oct 23.

During February 12-October 15, 2020, the coronavirus disease 2019 (COVID-19) pandemic resulted in approximately 7,900,000 aggregated reported cases and approximately 216,000 deaths in the United States.* Among COVID-19-associated deaths reported to national case surveillance during February 12-May 18, persons aged ≥65 years and members of racial and ethnic minority groups were disproportionately represented (1). This report describes demographic and geographic trends in COVID-19-associated deaths reported to the National Vital Statistics System (NVSS) during May 1-August 31, 2020, by 50 states and the District of Columbia. During this period, 114,411 COVID-19-associated deaths were reported. Overall, 78.2% of decedents were aged ≥65 years, and 53.3% were male; 51.3% were non-Hispanic White (White), 24.2% were Hispanic or Latino (Hispanic), and 18.7% were non-Hispanic Black (Black). The number of COVID-19-associated deaths decreased from 37,940 in May to 17,718 in June; subsequently, counts increased to 30,401 in July and declined to 28,352 in August. From May to August, the percentage distribution of COVID-19-associated deaths by U.S. Census region increased from 23.4% to 62.7% in the South and from 10.6% to 21.4% in the West. Over the same period, the percentage distribution of decedents who were Hispanic increased from 16.3% to 26.4%. COVID-19 remains a major public health threat regardless of age or race and ethnicity. Deaths continued to occur disproportionately among older persons and certain racial and ethnic minorities, particularly among Hispanic persons. These results can inform public health messaging and mitigation efforts focused on prevention and early detection of infection among disproportionately affected groups.
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http://dx.doi.org/10.15585/mmwr.mm6942e1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583501PMC
October 2020

Excess Deaths Associated with COVID-19, by Age and Race and Ethnicity - United States, January 26-October 3, 2020.

MMWR Morb Mortal Wkly Rep 2020 Oct 23;69(42):1522-1527. Epub 2020 Oct 23.

National Center for Health Statistics, CDC.

As of October 15, 216,025 deaths from coronavirus disease 2019 (COVID-19) have been reported in the United States*; however, this number might underestimate the total impact of the pandemic on mortality. Measures of excess deaths have been used to estimate the impact of public health pandemics or disasters, particularly when there are questions about underascertainment of deaths directly attributable to a given event or cause (1-6). Excess deaths are defined as the number of persons who have died from all causes, in excess of the expected number of deaths for a given place and time. This report describes trends and demographic patterns in excess deaths during January 26-October 3, 2020. Expected numbers of deaths were estimated using overdispersed Poisson regression models with spline terms to account for seasonal patterns, using provisional mortality data from CDC's National Vital Statistics System (NVSS) (7). Weekly numbers of deaths by age group and race/ethnicity were assessed to examine the difference between the weekly number of deaths occurring in 2020 and the average number occurring in the same week during 2015-2019 and the percentage change in 2020. Overall, an estimated 299,028 excess deaths have occurred in the United States from late January through October 3, 2020, with two thirds of these attributed to COVID-19. The largest percentage increases were seen among adults aged 25-44 years and among Hispanic or Latino (Hispanic) persons. These results provide information about the degree to which COVID-19 deaths might be underascertained and inform efforts to prevent mortality directly or indirectly associated with the COVID-19 pandemic, such as efforts to minimize disruptions to health care.
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http://dx.doi.org/10.15585/mmwr.mm6942e2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7583499PMC
October 2020

The Impact of the Pregnancy Checkbox and Misclassification on Maternal Mortality Trends in the United States, 1999-2017.

Vital Health Stat 3 2020 Jan(44):1-61

Maternal mortality is a critical indicator of population health in both the United States and internationally (1-3). Monitoring maternal mortality over time is important to evaluate progress in improving maternal health in the United States, to make international comparisons, and to examine differences and inequities by demographic subgroup (3). Substantial disparities in maternal mortality exist by race and Hispanic origin and age in the United States (4-6). Maternal and pregnancy-related mortality rates for non-Hispanic black women are approximately three times the rates for non-Hispanic white women, while women aged 40 and over have the highest maternal mortality rates compared with other age groups (4,6,7).
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January 2020

Trends in Intentional and Unintentional Opioid Overdose Deaths in the United States, 2000-2017.

JAMA 2019 12;322(23):2340-2342

National Institute on Drug Abuse, Bethesda, Maryland.

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http://dx.doi.org/10.1001/jama.2019.16566DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6990824PMC
December 2019

Healthy People 2020: Rural Areas Lag In Achieving Targets For Major Causes Of Death.

Health Aff (Millwood) 2019 12;38(12):2027-2031

Melonie Heron is a health scientist in the Division of Vital Statistics, NCHS.

For the period 2007-17 rural death rates were higher than urban rates for the seven major causes of death analyzed, and disparities widened for five of the seven. In 2017 urban areas had met national targets for three of the seven causes, while rural areas had met none of the targets.
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http://dx.doi.org/10.1377/hlthaff.2019.00915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365241PMC
December 2019

Urban-Rural Infant Mortality Disparities by Race and Ethnicity and Cause of Death.

Am J Prev Med 2020 02 15;58(2):254-260. Epub 2019 Nov 15.

Office of Epidemiology and Research, Maternal and Child Health Bureau, Health Resources and Services Administration, U.S. Department of Health and Human Services, Rockville, Maryland.

Introduction: Infant mortality rates are higher in nonmetropolitan areas versus large metropolitan areas. Variation by race/ethnicity and cause of death has not been assessed. Urban-rural infant mortality rate differences were quantified by race/ethnicity and cause of death.

Methods: National Vital Statistics System linked birth/infant death data (2014-2016) were analyzed in 2019 by 3 urban-rural county classifications: large metropolitan, medium/small metropolitan, and nonmetropolitan. Excess infant mortality rates (rate differences) by urban-rural classification were calculated relative to large metropolitan areas overall and for each racial/ethnic group. The number of excess deaths, population attributable fraction, and proportion of excess deaths attributable to underlying causes of death was calculated.

Results: Nonmetropolitan areas had the highest excess infant mortality rate overall. Excess infant mortality rates were substantially lower for Hispanic infants than other races/ethnicities. Overall, 7.4% of infant deaths would be prevented if all areas had the infant mortality rate of large metropolitan areas. With more than half of births occurring outside of large metropolitan areas, the population attributable fraction was highest for American Indian/Alaska Natives (20.3%) and whites, non-Hispanic (14.3%). Excess infant mortality rates in both nonmetropolitan and medium/small metropolitan areas were primarily attributable to sudden unexpected infant deaths (42.3% and 31.9%) and congenital anomalies (30.1% and 26.8%). This pattern was consistent for all racial/ethnic groups except black, non-Hispanic infants, for whom preterm-related and sudden unexpected infant deaths accounted for the largest share of excess infant mortality rates.

Conclusions: Infant mortality increases with rurality, and excess infant mortality rates are predominantly attributable to sudden unexpected infant deaths and congenital anomalies, with differences by race/ethnicity regarding magnitude and cause of death.
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http://dx.doi.org/10.1016/j.amepre.2019.09.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980981PMC
February 2020

Potentially Excess Deaths from the Five Leading Causes of Death in Metropolitan and Nonmetropolitan Counties - United States, 2010-2017.

MMWR Surveill Summ 2019 11 8;68(10):1-11. Epub 2019 Nov 8.

Problem/condition: A 2017 report quantified the higher percentage of potentially excess (or preventable) deaths in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas. In that report, CDC compared national, regional, and state estimates of potentially excess deaths among the five leading causes of death in nonmetropolitan and metropolitan counties for 2010 and 2014. This report enhances the geographic detail by using the six levels of the 2013 National Center for Health Statistics (NCHS) urban-rural classification scheme for counties and extending estimates of potentially excess deaths by annual percent change (APC) and for additional years (2010-2017). Trends were tested both with linear and quadratic terms.

Period Covered: 2010-2017.

Description Of System: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate potentially excess deaths from the five leading causes of death among persons aged <80 years. CDC's NCHS urban-rural classification scheme for counties was used to categorize the deaths according to the urban-rural county classification level of the decedent's county of residence (1: large central metropolitan [most urban], 2: large fringe metropolitan, 3: medium metropolitan, 4: small metropolitan, 5: micropolitan, and 6: noncore [most rural]). Potentially excess deaths were defined as deaths among persons aged <80 years that exceeded the number expected if the death rates for each cause in all states were equivalent to those in the benchmark states (i.e., the three states with the lowest rates). Potentially excess deaths were calculated separately for the six urban-rural county categories nationally, the 10 U.S. Department of Health and Human Services public health regions, and the 50 states and District of Columbia.

Results: The number of potentially excess deaths among persons aged <80 years in the United States increased during 2010-2017 for unintentional injuries (APC: 11.2%), decreased for cancer (APC: -9.1%), and remained stable for heart disease (APC: 1.1%), chronic lower respiratory disease (CLRD) (APC: 1.7%), and stroke (APC: 0.3). Across the United States, percentages of potentially excess deaths from the five leading causes were higher in nonmetropolitan counties in all years during 2010-2017. When assessed by the six urban-rural county classifications, percentages of potentially excess deaths in the most rural counties (noncore) were consistently higher than in the most urban counties (large central metropolitan) for the study period. Potentially excess deaths from heart disease increased most in micropolitan counties (APC: 2.5%) and decreased most in large fringe metropolitan counties (APC: -1.1%). Potentially excess deaths from cancer decreased in all county categories, with the largest decreases in large central metropolitan (APC: -16.1%) and large fringe metropolitan (APC: -15.1%) counties. In all county categories, potentially excess deaths from the five leading causes increased, with the largest increases occurring in large central metropolitan (APC: 18.3%), large fringe metropolitan (APC: 17.1%), and medium metropolitan (APC: 11.1%) counties. Potentially excess deaths from CLRD decreased most in large central metropolitan counties (APC: -5.6%) and increased most in micropolitan (APC: 3.7%) and noncore (APC: 3.6%) counties. In all county categories, potentially excess deaths from stroke exhibited a quadratic trend (i.e., decreased then increased), except in micropolitan counties, where no change occurred. Percentages of potentially excess deaths also differed among and within public health regions and across states by urban-rural county classification during 2010-2017.

Interpretation: Nonmetropolitan counties had higher percentages of potentially excess deaths from the five leading causes than metropolitan counties during 2010-2017 nationwide, across public health regions, and in the majority of states. The gap between the most rural and most urban counties for potentially excess deaths increased during 2010-2017 for three causes of death (cancer, heart disease, and CLRD), decreased for unintentional injury, and remained relatively stable for stroke. Urban and suburban counties (large central metropolitan and large fringe metropolitan, medium metropolitan, and small metropolitan) experienced increases in potentially excess deaths from unintentional injury during 2010-2017, leading to a narrower gap between the already high (approximately 55%) percentage of excess deaths in noncore and micropolitan counties.

Public Health Action: Routine tracking of potentially excess deaths by urban-rural county classification might help public health departments and decision-makers identify and monitor public health problems and focus interventions to reduce potentially excess deaths in these areas.
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http://dx.doi.org/10.15585/mmwr.ss6810a1DOI Listing
November 2019

Beyond birth outcomes: Interpregnancy interval and injury-related infant mortality.

Paediatr Perinat Epidemiol 2019 09 12;33(5):360-370. Epub 2019 Sep 12.

Office of Population Affairs, Office of the Assistant Secretary for Health, U.S. Department of Health and Human Services, Rockville, MD.

Background: Several studies have examined the association between IPI and birth outcomes, but few have explored the association between interpregnancy interval (IPI) and postnatal outcomes.

Objective: We examined the association between IPI and injury-related infant mortality, a leading cause of postneonatal mortality.

Methods: We used 2011-2015 US period-linked birth-infant death vital statistics data to generate a multiyear birth cohort of non-first-born singleton births (N = 9 782 029). IPI was defined as the number of months between a live birth and the start of the pregnancy leading to the next live birth. Causes of death in the first year of life were identified using ICD-10 codes. Hazard ratios (HR) for IPI categories were estimated using Cox proportional hazards models adjusted for birth order, county poverty level, and maternal characteristics (marital status, race/ethnicity, education, age at previous birth).

Results: After adjustment, overall infant mortality (48.1 per 10 000 births) was higher for short and long IPIs compared with IPI 18-23 months (reference): <6, aHR 1.61, 95% CI 1.54, 1.68; 6-11, aHR 1.22, 95% CI 1.17, 1.26; and 60+ months, aHR 1.12, 95% CI 1.08, 1.16. In comparison, the risk of injury-related infant mortality (4.4 per 10 000 births) decreased with longer IPIs: <6, aHR 1.77, 95% CI 1.55, 2.01; 6-11, aHR 1.41, 95% CI 1.25, 1.59; 12-17, aHR 1.25, 95% CI 1.10, 1.41; 24-59, aHR 0.78, 95% CI 0.69, 0.87; and 60+ months, aHR 0.55, 95% CI 0.48, 0.62.

Conclusion: Unlike overall infant mortality, injury-related infant mortality decreased with IPI length. While injury-related deaths are rare, these patterns suggest that the timing between births may be a marker of risk for fatal infant injuries. The first year postpartum may be an ideal time for the delivery of evidence-based injury prevention programmes as well as family planning services.
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http://dx.doi.org/10.1111/ppe.12575DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913028PMC
September 2019

Unintentional Injury Death Rates in Rural and Urban Areas: United States, 1999-2017.

NCHS Data Brief 2019 Jul(343):1-8

Unintentional injury is a leading cause of death in the United States (1). Higher death rates for unintentional injury have been reported in rural areas compared with urban areas (2-4). This report describes trends in the death rates for unintentional injuries and three leading causes of deaths due to unintentional injuries (motor vehicle traffic, drug overdose, and falls) from 1999 through 2017. Given an observed increase in overall unintentional injury rates starting in 2014 (5), differences in death rates are described by urbanization level (rural, small metropolitan [metro], large fringe metro, and large central metro) for the leading causes of unintentional injury deaths for 2014 and 2017.
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July 2019

Good practices for the design, analysis, and interpretation of observational studies on birth spacing and perinatal health outcomes.

Paediatr Perinat Epidemiol 2019 01 12;33(1):O15-O24. Epub 2018 Oct 12.

Office of Population Affairs, Office of the Assistant Secretary for Health, Rockville, Maryland.

Background: Meta-analyses of observational studies have shown that women with a shorter interpregnancy interval (the time from delivery to start of a subsequent pregnancy) are more likely to experience adverse pregnancy outcomes, such as preterm delivery or small for gestational age birth, than women who space their births further apart. However, the studies used to inform these estimates have methodological shortcomings.

Methods: In this commentary, we summarise the discussions of an expert workgroup describing good practices for the design, analysis, and interpretation of observational studies of interpregnancy interval and adverse perinatal health outcomes.

Results: We argue that inferences drawn from research in this field will be improved by careful attention to elements such as: (a) refining the research question to clarify whether the goal is to estimate a causal effect vs describe patterns of association; (b) using directed acyclic graphs to represent potential causal networks and guide the analytic plan of studies seeking to estimate causal effects; (c) assessing how miscarriages and pregnancy terminations may have influenced interpregnancy interval classifications; (d) specifying how key factors such as previous pregnancy loss, pregnancy intention, and maternal socio-economic position will be considered; and (e) examining if the association between interpregnancy interval and perinatal outcome differs by factors such as maternal age.

Conclusion: This commentary outlines the discussions of this recent expert workgroup, and describes several suggested principles for study design and analysis that could mitigate many potential sources of bias.
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http://dx.doi.org/10.1111/ppe.12512DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6378590PMC
January 2019

Report of the Office of Population Affairs' expert work group meeting on short birth spacing and adverse pregnancy outcomes: Methodological quality of existing studies and future directions for research.

Paediatr Perinat Epidemiol 2019 01 9;33(1):O5-O14. Epub 2018 Oct 9.

Office of Population Affairs, Office of the Assistant Secretary for Health, Rockville, Maryland.

Background: The World Health Organization (WHO) recommends that women wait at least 24 months after a livebirth before attempting a subsequent pregnancy to reduce the risk of adverse maternal, perinatal, and infant health outcomes. However, the applicability of the WHO recommendations for women in the United States is unclear, as breast feeding, nutrition, maternal age at first birth, and total fertility rate differs substantially between the United States and the low- and middle-resource countries upon which most of the evidence is based.

Methods: To inform guideline development for birth spacing specific to women in the United States, the Office of Population Affairs (OPA) convened an expert work group meeting in Washington, DC, on 14-15 September 2017 among reproductive, perinatal, paediatric, social, and public health epidemiologists; obstetrician-gynaecologists; biostatisticians; and experts in evidence synthesis related to women's health.

Results: Presentations and discussion topics included the methodological quality of existing studies, evaluation of the evidence for causal effects of short interpregnancy intervals on adverse perinatal and maternal health outcomes, good practices for future research, and identification of research gaps and priorities for future work.

Conclusions: This report provides an overview of the presentations, discussions, and conclusions from the expert work group meeting.
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http://dx.doi.org/10.1111/ppe.12504DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6378402PMC
January 2019

Estimating Usual Dietary In take From National Health and Nut rition Examination Survey Data Using the National Cancer Institute Method.

Vital Health Stat 2 2018 Feb(178):1-63

Dietary recommendations are intended to be met based on dietary intake over long periods, as associations between diet and health result from habitual intake, not a single eating occasion or day of intake. Measuring usual intake directly is impractical for large population-based surveys due to the respondent burden associated with reporting habitual intake over longer periods. Therefore, analytical techniques were developed to estimate usual intake using as few as 2 days of 24-hour dietary recall data. With National Health and Nutrition Examination Survey (NHANES) data, this report demonstrates how to estimate usual intake using the National Cancer Institute (NCI). This report demonstrates how to estimate the usual intake of nutrients consumed daily or episodically using NHANES data. Means, percentiles, and the percentages above or below specified Dietary Reference Intake (DRI) values for given day, within-person mean (WPM), and estimates of usual intake are presented. Consistent with previous analyses, mean intakes were similar across methods. However, the distributions estimated by nonusual intake methods were wider compared with the NCI Method, which can lead to misclassification of the percentage of the population above or below certain DRIs. Use of NHANES data to examine the proportion of the population at risk of insufficiency or excess of certain nutrients, with methods like given day and WPM that do not address within-person variation, may lead to biased estimates.
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February 2018

Estimating Usual Dietary In take From National Health and Nut rition Examination Survey Data Using the National Cancer Institute Method.

Vital Health Stat 2 2018 Feb(178):1-63

Dietary recommendations are intended to be met based on dietary intake over long periods, as associations between diet and health result from habitual intake, not a single eating occasion or day of intake. Measuring usual intake directly is impractical for large population-based surveys due to the respondent burden associated with reporting habitual intake over longer periods. Therefore, analytical techniques were developed to estimate usual intake using as few as 2 days of 24-hour dietary recall data. With National Health and Nutrition Examination Survey (NHANES) data, this report demonstrates how to estimate usual intake using the National Cancer Institute (NCI). This report demonstrates how to estimate the usual intake of nutrients consumed daily or episodically using NHANES data. Means, percentiles, and the percentages above or below specified Dietary Reference Intake (DRI) values for given day, within-person mean (WPM), and estimates of usual intake are presented. Consistent with previous analyses, mean intakes were similar across methods. However, the distributions estimated by nonusual intake methods were wider compared with the NCI Method, which can lead to misclassification of the percentage of the population above or below certain DRIs. Use of NHANES data to examine the proportion of the population at risk of insufficiency or excess of certain nutrients, with methods like given day and WPM that do not address within-person variation, may lead to biased estimates.
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February 2018

Singleton Low Birthweight Rates, by Race and Hispanic Origin: United States, 2006-2016.

NCHS Data Brief 2018 Mar(306):1-8

Low birthweight (LBW) is among the leading causes of infant death in the United States (1). LBW infants are also more likely to have health problems (2). After reaching its highest level in four decades, the LBW rate among all births declined from 2006 to 2014 (3,4), but the trend reversed in 2015 and 2016 when the LBW rate increased (4), moving further away from the Healthy People 2020 goal of reducing LBW rates to 7.8% of live births (5). This report shows trends in LBW, moderately low birthweight (MLBW), and very low birthweight (VLBW) by race and Hispanic origin from 2006 to 2016 for singleton births only, as rates of multiple births can impact LBW rates (4,6).
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March 2018

Singleton Low Birthweight Rates, by Race and Hispanic Origin: United States, 2006-2016.

NCHS Data Brief 2018 Mar(306):1-8

Low birthweight (LBW) is among the leading causes of infant death in the United States (1). LBW infants are also more likely to have health problems (2). After reaching its highest level in four decades, the LBW rate among all births declined from 2006 to 2014 (3,4), but the trend reversed in 2015 and 2016 when the LBW rate increased (4), moving further away from the Healthy People 2020 goal of reducing LBW rates to 7.8% of live births (5). This report shows trends in LBW, moderately low birthweight (MLBW), and very low birthweight (VLBW) by race and Hispanic origin from 2006 to 2016 for singleton births only, as rates of multiple births can impact LBW rates (4,6).
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March 2018

Trends in Risk of Pregnancy Loss Among US Women, 1990-2011.

Paediatr Perinat Epidemiol 2018 01 20;32(1):19-29. Epub 2017 Oct 20.

Office of the Center Director, National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD.

Background: Pregnancy loss can have physical and psychological consequences for women and their families. Though a previous study described an increase in the risk of self-reported pregnancy loss from 1970 to 2000, more recent examinations from population-based data of US women are lacking.

Methods: We used data from the 1995, 2002, 2006-2010, 2011-2015 National Survey of Family Growth on self-reported pregnancy loss (miscarriage, stillbirth, ectopic pregnancy) among US women (15-44 years) who reported at least one pregnancy conceived during 1990-2011 that did not result in induced termination (n = 20 012 women; n = 42 526 pregnancies). Trends in the risk of self-reported pregnancy loss and early pregnancy loss (<12 weeks) were estimated, separately, by year of pregnancy conception (limited to 1990-2011 to ensure a sufficient sample of pregnancies for each year and maternal age group) using log-Binomial and Poisson models, adjusted for maternal- and pregnancy-related factors.

Results: Among all self-reported pregnancies, excluding induced terminations, the risk of pregnancy loss was 19.7% and early pregnancy loss was 13.5% during 1990-2011. Risk of pregnancy loss increased by a relative 2% (rate ratio [RR] 1.02, 95% confidence interval [CI] 1.01, 1.02) per year in unadjusted models and 1% per year (RR 1.01, 95% CI 1.00, 1.02) during 1990-2011, after adjustment for maternal characteristics and pregnancy-related factors. In general, trends were similar for early pregnancy loss.

Conclusion: From 1990 to 2011, risk of self-reported pregnancy loss increased among US women. Further work is needed to better understand the drivers of this increase in reported pregnancy loss in the US.
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http://dx.doi.org/10.1111/ppe.12417DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771868PMC
January 2018

Contribution of weight status to asthma prevalence racial disparities, 2-19 year olds, 1988-2014.

Ann Epidemiol 2017 08 14;27(8):472-478.e3. Epub 2017 Jul 14.

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD; US Public Health Service, Rockville, MD.

Purpose: Racial disparities in childhood asthma prevalence increased after the 1990s. Obesity, which also varies by race/ethnicity, is an asthma risk factor but its contribution to asthma prevalence disparities is unknown.

Methods: We analyzed nationally representative National Health Examination and Nutrition Survey data for 2-19 year olds with logistic regression and decomposition analyses to assess the contributions of weight status to racial disparities in asthma prevalence, controlling for sex, age, and income status.

Results: From 1988-1994 to 2011-2014, asthma prevalence increased more among non-Hispanic black (NHB) (8.4% to 18.0%) than non-Hispanic white (NHW) youth (7.2% to 10.3%). Logistic regression showed that obesity was an asthma risk factor for all groups but that a three-way "weight status-race/ethnicity-time" interaction was not significant. That is, weight status did not modify the race/ethnicity association with asthma over time. In decomposition analyses, weight status had a small contribution to NHB/NHW asthma prevalence disparities but most of the disparity remained unexplained by weight status or other asthma risk factors (sex, age and income status).

Conclusions: NHB youth had a greater asthma prevalence increase from 1988-1994 to 2011-2014 than NHW youth. Most of the racial disparity in asthma prevalence remained unexplained after considering weight status and other characteristics.
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http://dx.doi.org/10.1016/j.annepidem.2017.07.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413506PMC
August 2017

Interpregnancy Interval and Adverse Pregnancy Outcomes: An Analysis of Successive Pregnancies.

Obstet Gynecol 2017 08;130(2):464

Mortality Statistics Branch, Division of Vital Statistics, National Center for Health Statistics, Hyattsville, Maryland.

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http://dx.doi.org/10.1097/AOG.0000000000002173DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5592837PMC
August 2017

Birth Order and Injury-Related Infant Mortality in the U.S.

Am J Prev Med 2017 Oct 27;53(4):412-420. Epub 2017 Jun 27.

Office on Women's Health, Office of the Assistant Secretary for Health, U.S. DHHS, Washington, District of Columbia.

Introduction: The purpose of this study was to evaluate the risk of death during the first year of life due to injury, such as unintentional injury and homicide, by birth order in the U.S.

Methods: Using national birth cohort-linked birth-infant death data (births, 2000-2010; deaths, 2000-2011), risks of infant mortality due to injury in second-, third-, fourth-, and fifth or later-born singleton infants were compared with first-born singleton infants. Risk ratios were estimated using log-binomial models adjusted for maternal age, marital status, race/ethnicity, and education. The statistical analyses were conducted in 2016.

Results: Approximately 40%, 32%, 16%, 7%, and 4% of singleton live births were first, second, third, fourth, and fifth or later born, respectively. From 2000 to 2011, a total of 15,866 infants died as a result of injury (approximately 1,442 deaths per year). Compared with first-born infants (2.9 deaths per 10,000 live births), second or later-born infants were at increased risk of infant mortality due to injury (second, 3.6 deaths; third, 4.2 deaths; fourth, 4.8 deaths; fifth or later, 6.4 deaths). The corresponding adjusted risk ratios were as follows: second, 1.84 (95% CI=1.76, 1.91); third, 2.42 (95% CI=2.30, 2.54); fourth, 2.96 (95% CI=2.77, 3.16); and fifth or later, 4.26 (95% CI=3.96, 4.57).

Conclusions: Singleton infants born second or later were at increased risk of mortality due to injury during their first year of life in the U.S. This study's findings highlight the importance of investigating underlying mechanisms behind this increased risk.
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http://dx.doi.org/10.1016/j.amepre.2017.04.018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5697982PMC
October 2017

Spatiotemporal trends in teen birth rates in the USA, 2003-2012.

J R Stat Soc Ser A Stat Soc 2018 01 19;181(1):35-58. Epub 2017 Jan 19.

National Center for Health Statistics, Hyattsville, USA.

The objective of this analysis was to explore temporal and spatial variation in teen birth rates TBRs across counties in the USA, from 2003 to 2012, by using hierarchical Bayesian models. Prior examination of spatiotemporal variation in TBRs has been limited by the reliance on large-scale geographies such as states, because of the potential instability in TBRs at smaller geographical scales such as counties. We implemented hierarchical Bayesian models with space-time interaction terms and spatially structured and unstructured random effects to produce smoothed county level TBR estimates, allowing for examination of spatiotemporal patterns and trends in TBRs at a smaller geographic scale across the USA. The results may help to highlight US counties where TBRs are higher or lower and to inform efforts to reduce birth rates to adolescents in the USA further.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5464734PMC
http://dx.doi.org/10.1111/rssa.12266DOI Listing
January 2018

HUD Housing Assistance Associated With Lower Uninsurance Rates And Unmet Medical Need.

Health Aff (Millwood) 2017 06;36(6):1016-1023

Lauren M. Rossen is a health statistician in the Division of Vital Statistics at the National Center for Health Statistics.

To investigate whether receiving US Department of Housing and Urban Development (HUD) housing assistance is associated with improved access to health care, we analyzed data on nondisabled adults ages 18-64 who responded to the 2004-12 National Health Interview Survey that were linked with administrative data from HUD for the period 2002-14. To account for potential selection bias, we compared access to care between respondents who were receiving HUD housing assistance at the time of the survey interview (current recipients) and those who received HUD assistance within twenty-four months of completing the survey interview (future recipients). Receiving assistance was associated with lower uninsurance rates: 31.8 percent of current recipients were uninsured, compared to 37.2 percent of future recipients. Rates of unmet need for health care due to cost were similarly lower for current recipients than for future recipients. No effect of receiving assistance was observed on having a usual source of care. These findings provide evidence that supports the effectiveness of housing assistance in improving health care access.
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http://dx.doi.org/10.1377/hlthaff.2016.1152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5603165PMC
June 2017

Hot spots, cluster detection and spatial outlier analysis of teen birth rates in the U.S., 2003-2012.

Spat Spatiotemporal Epidemiol 2017 06 27;21:67-75. Epub 2017 Mar 27.

RADARS SYSTEM/Rocky Mountain Poison & Drug Center (RMPDC)/A Division of Denver Health, 990 Bannock Street M/C 0180 | Denver, CO 80204, USA.

Teen birth rates have evidenced a significant decline in the United States over the past few decades. Most of the states in the US have mirrored this national decline, though some reports have illustrated substantial variation in the magnitude of these decreases across the U.S. Importantly, geographic variation at the county level has largely not been explored. We used National Vital Statistics Births data and Hierarchical Bayesian space-time interaction models to produce smoothed estimates of teen birth rates at the county level from 2003-2012. Results indicate that teen birth rates show evidence of clustering, where hot and cold spots occur, and identify spatial outliers. Findings from this analysis may help inform efforts targeting the prevention efforts by illustrating how geographic patterns of teen birth rates have changed over the past decade and where clusters of high or low teen birth rates are evident.
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http://dx.doi.org/10.1016/j.sste.2017.03.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5618106PMC
June 2017

Housing Assistance Programs and Adult Health in the United States.

Am J Public Health 2017 04 16;107(4):571-578. Epub 2017 Feb 16.

Andrew Fenelon is with the Department of Health Services Administration, University of Maryland, College Park. Patrick Mayne is with the Department of Sociology, Brown University, Providence, RI. Alan E. Simon is with the Office of the Assistant Secretary for Health, US Department of Health and Human Services, Washington, DC. Lauren M. Rossen and Patricia Lloyd are with the National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD. Veronica Helms, Jon Sperling, and Barry L. Steffen are with the Office of Policy Development and Research, US Department of Housing and Urban Development, Washington, DC.

Objectives: To examine whether access to housing assistance is associated with better health among low-income adults.

Methods: We used National Health Interview Survey data (1999-2012) linked to US Department of Housing and Urban Development (HUD) administrative records (1999-2014) to examine differences in reported fair or poor health and psychological distress. We used multivariable models to compare those currently receiving HUD housing assistance (public housing, housing choice vouchers, and multifamily housing) with those who will receive housing assistance within 2 years (the average duration of HUD waitlists) to account for selection into HUD assistance.

Results: We found reduced odds of fair or poor health for current public housing (odds ratio [OR] = 0.77; 95% confidence interval [CI] = 0.57, 0.97) and multifamily housing (OR = 0.75; 95% CI = 0.60, 0.95) residents compared with future residents. Public housing residents also had reduced odds of psychological distress (OR = 0.59; 95% CI = 0.40, 0.86). These differences were not mediated by neighborhood-level characteristics, and we did not find any health benefits for current housing choice voucher recipients.

Conclusions: Housing assistance is associated with improved health and psychological well-being for individuals entering public housing and multifamily housing programs.
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http://dx.doi.org/10.2105/AJPH.2016.303649DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5343706PMC
April 2017

Plurality of Birth and Infant Mortality Due to External Causes in the United States, 2000-2010.

Am J Epidemiol 2017 03;185(5):335-344

Risk of death during the first year of life due to external causes, such as unintentional injury and homicide, may be higher among twins and higher-order multiples than among singletons in the United States. We used national birth cohort linked birth-infant death data (2000-2010) to evaluate the risk of infant mortality due to external causes in multiples versus singletons in the United States. Risk of death from external causes during the study period was 3.6 per 10,000 live births in singletons and 5.1 per 10,000 live births in multiples. Using log-binomial regression, the corresponding unadjusted risk ratio was 1.40 (95% confidence interval (CI): 1.30, 1.50). After adjustment for maternal age, marital status, race/ethnicity, and education, the risk ratio was 1.68 (95% CI: 1.56, 1.81). Infant deaths due to external causes were most likely to occur between 2 and 7 months of age. Applying inverse probability weighting and assuming a hypothetical intervention where no infants were low birth weight, the adjusted controlled direct effect of plurality on infant mortality due to external causes was 1.64 (95% CI: 1.39, 1.97). Twins and higher-order multiples were at greater risk of infant mortality due to external causes, particularly between 2 and 7 months of age, and this risk appeared to be mediated largely by factors other than low-birth-weight status.
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http://dx.doi.org/10.1093/aje/kww119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6700729PMC
March 2017

Leading Causes of Death in Nonmetropolitan and Metropolitan Areas- United States, 1999-2014.

MMWR Surveill Summ 2017 Jan 13;66(1):1-8. Epub 2017 Jan 13.

Center for Surveillance, Epidemiology, and Laboratory Services, CDC.

Problem/condition: Higher rates of death in nonmetropolitan areas (often referred to as rural areas) compared with metropolitan areas have been described but not systematically assessed.

Period Covered: 1999-2014 DESCRIPTION OF SYSTEM: Mortality data for U.S. residents from the National Vital Statistics System were used to calculate age-adjusted death rates and potentially excess deaths for nonmetropolitan and metropolitan areas for the five leading causes of death. Age-adjusted death rates included all ages and were adjusted to the 2000 U.S. standard population by the direct method. Potentially excess deaths are defined as deaths among persons aged <80 years that exceed the numbers that would be expected if the death rates of states with the lowest rates (i.e., benchmark states) occurred across all states. (Benchmark states were the three states with the lowest rates for each cause during 2008-2010.) Potentially excess deaths were calculated separately for nonmetropolitan and metropolitan areas. Data are presented for the United States and the 10 U.S. Department of Health and Human Services public health regions.

Results: Across the United States, nonmetropolitan areas experienced higher age-adjusted death rates than metropolitan areas. The percentages of potentially excess deaths among persons aged <80 years from the five leading causes were higher in nonmetropolitan areas than in metropolitan areas. For example, approximately half of deaths from unintentional injury and chronic lower respiratory disease in nonmetropolitan areas were potentially excess deaths, compared with 39.2% and 30.9%, respectively, in metropolitan areas. Potentially excess deaths also differed among and within public health regions; within regions, nonmetropolitan areas tended to have higher percentages of potentially excess deaths than metropolitan areas.

Interpretation: Compared with metropolitan areas, nonmetropolitan areas have higher age-adjusted death rates and greater percentages of potentially excess deaths from the five leading causes of death, nationally and across public health regions.

Public Health Action: Routine tracking of potentially excess deaths in nonmetropolitan areas might help public health departments identify emerging health problems, monitor known problems, and focus interventions to reduce preventable deaths in these areas.
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http://dx.doi.org/10.15585/mmwr.ss6601a1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829895PMC
January 2017

Potentially Preventable Deaths Among the Five Leading Causes of Death - United States, 2010 and 2014.

MMWR Morb Mortal Wkly Rep 2016 Nov 18;65(45):1245-1255. Epub 2016 Nov 18.

Death rates by specific causes vary across the 50 states and the District of Columbia.* Information on differences in rates for the leading causes of death among states might help state health officials determine prevention goals, priorities, and strategies. CDC analyzed National Vital Statistics System data to provide national and state-specific estimates of potentially preventable deaths among the five leading causes of death in 2014 and compared these estimates with estimates previously published for 2010. Compared with 2010, the estimated number of potentially preventable deaths changed (supplemental material at https://stacks.cdc.gov/view/cdc/42472); cancer deaths decreased 25% (from 84,443 to 63,209), stroke deaths decreased 11% (from 16,973 to 15,175), heart disease deaths decreased 4% (from 91,757 to 87,950), chronic lower respiratory disease (CLRD) (e.g., asthma, bronchitis, and emphysema) deaths increased 1% (from 28,831 to 29,232), and deaths from unintentional injuries increased 23% (from 36,836 to 45,331). A better understanding of progress made in reducing potentially preventable deaths in the United States might inform state and regional efforts targeting the prevention of premature deaths from the five leading causes in the United States.
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http://dx.doi.org/10.15585/mmwr.mm6545a1DOI Listing
November 2016

Teen Birth Rates for Urban and Rural Areas in the United States, 2007-2015.

NCHS Data Brief 2016 Nov(264):1-8

Key Findings: Data from the National Vital Statistics System •Birth rates for teenagers aged 15-19 declined in urban and rural counties from 2007 through 2015, with the largest declines in large urban counties and the smallest declines in rural counties. •From 2007 through 2015, the teen birth rate was lowest in large urban counties and highest in rural counties. •Declines in teen birth rates in all urban counties between 2007 and 2015 were largest in Arizona, Massachusetts, Connecticut, Minnesota, and Colorado, with 17 states experiencing a decline of 50% or more. •Declines in teen birth rates in all rural counties between 2007 and 2015 were largest (50% or more) in Colorado and Connecticut. •In 2015, teen birth rates were highest in rural counties and lowest in large urban counties for non-Hispanic white, non-Hispanic black, and Hispanic females. Teen birth rates have demonstrated an unprecedented decline in the United States since 2007 (1). Declines occurred in all states and among all major racial and Hispanic-origin groups, yet disparities by both geography and demographic characteristics persist (2,3). Although teen birth rates and related declines have been described by state, patterns by urban-rural location have not yet been examined. This report describes trends in teen birth rates in urban (metropolitan) and rural (nonmetropolitan) areas in the United States overall and by state from 2007 through 2015 and by race and Hispanic origin for 2015.
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November 2016

Income Inequality and US Children's Secondhand Smoke Exposure: Distinct Associations by Race-Ethnicity.

Nicotine Tob Res 2017 Nov;19(11):1292-1299

School of Public Health, Maryland Institute for Applied Environmental Health, University of Maryland, College Park, MD.

Introduction: Prior studies have found considerable racial and ethnic disparities in secondhand smoke (SHS) exposure. Although a number of individual-level determinants of this disparity have been identified, contextual determinants of racial and ethnic disparities in SHS exposure remain unexamined. The objective of this study was to examine disparities in serum cotinine in relation to area-level income inequality among 14 649 children from the National Health and Nutrition Examination Survey.

Methods: We fit log-normal regression models to examine disparities in serum cotinine in relation to Metropolitan Statistical Areas level income inequality among 14 649 nonsmoking children aged 3-15 from the National Health and Nutrition Examination Survey (1999-2012).

Result: Non-Hispanic black children had significantly lower serum cotinine than non-Hispanic white children (-0.26; 95% CI: -0.38, -0.15) in low income inequality areas, but this difference was attenuated in areas with high income inequality (0.01; 95% CI: -0.16, 0.18). Serum cotinine declined for non-Hispanic white and Mexican American children with increasing income inequality. Serum cotinine did not change as a function of the level of income inequality among non-Hispanic black children.

Conclusions: We have found evidence of differential associations between SHS exposure and income inequality by race and ethnicity. Further examination of environments which engender SHS exposure among children across various racial/ethnic subgroups can foster a better understanding of how area-level income inequality relates to health outcomes such as levels of SHS exposure and how those associations differ by race/ethnicity.

Implications: In the United States, the association between children's risk of SHS exposure and income inequality is modified by race/ethnicity in a manner that is inconsistent with theories of income inequality. In overall analysis this association appears to be as predicted by theory. However, race-specific analyses reveal that higher levels of income inequality are associated with lower levels of SHS exposure among white children, while levels of SHS exposure among non-Hispanic black children are largely invariant to area-level income inequality. Future examination of the link between income inequality and smoking-related health outcomes should consider differential associations across racial and ethnic subpopulations.
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http://dx.doi.org/10.1093/ntr/ntw293DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415442PMC
November 2017

Housing Assistance and Blood Lead Levels: Children in the United States, 2005-2012.

Am J Public Health 2016 11 15;106(11):2049-2056. Epub 2016 Sep 15.

Katherine A. Ahrens, Lauren M. Rossen, and Patricia C. Lloyd are with the Office of Analysis & Epidemiology, National Center for Health Statistics, Centers for Disease Control and Prevention, US Department of Health and Human Services, Hyattsville, MD. Barbara A. Haley is with the Office of Policy Development and Research, US Department of Housing and Urban Development, Washington, DC. Yutaka Aoki is with the Division of Health and Nutrition Examination Surveys, National Center for Health Statistics, Centers for Disease Control and Prevention, US Department of Health and Human Services, Hyattsville.

Objectives: To compare blood lead levels (BLLs) among US children aged 1 to 5 years according to receipt of federal housing assistance.

Methods: In our analyses, we used 2005 to 2012 data for National Health and Nutrition Examination Survey (NHANES) respondents that were linked to 1999 to 2014 administrative records from the US Department of Housing and Urban Development (HUD). After we restricted the analysis to children with family income-to-poverty ratios below 200%, we compared geometric mean BLLs and the prevalence of BLLs of 3 micrograms per deciliter or higher among children who were living in assisted housing at the time of their NHANES blood draw (n = 151) with data for children who did not receive housing assistance (n = 1099).

Results: After adjustment, children living in assisted housing had a significantly lower geometric mean BLL (1.44 µg/dL; 95% confidence interval [CI] = 1.31, 1.57) than comparable children who did not receive housing assistance (1.79 µg/dL; 95% CI = 1.59, 2.01; P < .01). The prevalence ratio for BLLs of 3 micrograms per deciliter or higher was 0.51 (95% CI = 0.33, 0.81; P < .01).

Conclusions: Children aged 1 to 5 years during 2005 to 2012 who were living in HUD-assisted housing had lower BLLs than expected given their demographic, socioeconomic, and family characteristics.
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http://dx.doi.org/10.2105/AJPH.2016.303432DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5055789PMC
November 2016