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To examine changes in death rates by demographic group and by the leading causes of death in U.S. persons 1 to 24 years of age during the COVID-19 pandemic. A retrospective cross-sectional study using mortality data from the National Vital Statistics System from April 2017 to March 2023. Pre-pandemic death rates were compared with death rates during the pandemic overall, by race/ethnicity, age, sex, and cause group. Age-adjusted death rates in young persons 1–24 years of age increased by 14.3% during the pandemic. Injury-related causes accounted for 78.2% of the increase, driven mainly by increases in homicides and unintentional injuries related to drug overdose, firearms, and motor-vehicle traffic crashes. Non-Hispanic Black and Hispanic teens and young adults experienced the largest increases in deaths overall and across the leading causes of death. During the COVID-19 pandemic, injury-related causes accounted for the majority of the increases in deaths in children and young adults, driven mainly by firearms, drug overdoses, and motor vehicle traffic crashes. Findings highlight the importance of understanding the drivers of these marked increases in injury-related mortality and the need for injury prevention efforts among children even in the context of an infectious disease pandemic. [ABSTRACT FROM AUTHOR]

Background: Trends in the prevalence of hepatitis C virus (HCV) infection among women delivering live births may differ in rural vs. urban areas of the United States, but estimation of trends based on observed counts may lead to unstable estimates in rural counties due to small numbers. Objectives: The objective of the study was to use small area estimation methods to provide updated county‐level prevalence estimates and, for the first time, trends in maternal HCV infection among live births by county‐level rurality. Methods: Cross‐sectional natality data from 2016 to 2020 were used to estimate maternal hepatitis C prevalence using hierarchical Bayesian models with spatiotemporal random effects to produce annual county‐level estimates of maternal HCV infection and trends over time. Models included a 6‐level rural–urban county classification, year, maternal characteristics and county‐specific covariates. Data were analysed in 2022. Results: There were 90,764/18,905,314 live births (4.8 per 1000) with HCV infection reported on the birth certificate. Hepatitis C prevalence was higher among rural counties as compared to urban counties. Rural counties had the largest annual increases in maternal hepatitis C prevalence (per 1000 births) from 2016 to 2020 (micropolitan: 0.39; noncore: 0.40), with smaller increases among less densely populated urban counties (medium metro: 0.28; small metro: 0.28) and urban counties (large central metro:0.11; large fringe metro: 0.14). Conclusions: The prevalence of maternal HCV infection was the highest in rural counties, and rural counties saw the greatest average prevalence increase during 2016–2020. County‐level data can help in monitoring rural–urban trends in maternal HCV infection to reduce geographic disparities. [ABSTRACT FROM AUTHOR]

It has been difficult to measure rural-urban differences in maternal mortality ratios (MMRs) in the United States in recent years because of the incremental adoption of a pregnancy status checkbox on the standard US death certificate. Using 1999–2017 mortality and birth data, we examined the impact of the pregnancy checkbox on MMRs according to urbanicity of residence (large urban area, medium/small urban area, or rural area), using log-binomial regression models to predict trends that would have been observed if all states had adopted the checkbox as of 1999. Implementation of the checkbox resulted in an average estimated increase of 7.5 maternal deaths per 100,000 live births (95% confidence interval (CI): 6.3, 8.8) in large urban areas (a 76% increase), 11.6 (95% CI: 9.6, 13.6) in medium/small urban areas (a 113% increase), and 16.6 (95% CI: 12.9, 20.3) in rural areas (a 107% increase), compared with MMRs prior to the checkbox. Assuming that all states had the checkbox as of 1999, demographic-factor–adjusted predicted MMRs increased in rural areas, declined in large urban areas, and did not change in medium/small urban areas. However, trends and urban-rural differences were substantially attenuated when analyses were limited to direct/specific causes of maternal death, which are probably subject to less misclassification. Accurate ascertainment of maternal deaths, particularly in rural areas, is important for reducing disparities in maternal mortality. [ABSTRACT FROM AUTHOR]

Background: In the United States, infection with SARS‐CoV‐2 caused 380,000 reported deaths from March to December 2020. Methods: We adapted the Moving Epidemic Method to all‐cause mortality data from the United States to assess the severity of the COVID‐19 pandemic across age groups and all 50 states. By comparing all‐cause mortality during the pandemic with intensity thresholds derived from recent, historical all‐cause mortality, we categorized each week from March to December 2020 as either low severity, moderate severity, high severity, or very high severity. Results: Nationally for all ages combined, all‐cause mortality was in the very high severity category for 9 weeks. Among people 18 to 49 years of age, there were 29 weeks of consecutive very high severity mortality. Forty‐seven states, the District of Columbia, and New York City each experienced at least 1 week of very high severity mortality for all ages combined. Conclusions: These periods of very high severity of mortality during March through December 2020 are likely directly or indirectly attributable to the COVID‐19 pandemic. This method for standardized comparison of severity over time across different geographies and demographic groups provides valuable information to understand the impact of the COVID‐19 pandemic and to identify specific locations or subgroups for deeper investigations into differences in severity. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study used data from the National Vital Statistics System Mortality to evaluate trends in US drug overdose deaths involving opioids certified as unintentional, suicide, or undetermined intent. [ABSTRACT FROM AUTHOR]

Introduction: Understanding the geographic patterns of suicide can help inform targeted prevention efforts. Although state-level variation in age-adjusted suicide rates has been well documented, trends at the county-level have been largely unexplored. This study uses small area estimation to produce stable county-level estimates of suicide rates to examine geographic, temporal, and urban-rural patterns in suicide from 2005 to 2015.Methods: Using National Vital Statistics Underlying Cause of Death Files (2005-2015), hierarchical Bayesian models were used to estimate suicide rates for 3,140 counties. Model-based suicide rate estimates were mapped to explore geographic and temporal patterns and examine urban-rural differences. Analyses were conducted in 2016-2017.Results: Posterior predicted mean county-level suicide rates increased by >10% from 2005 to 2015 for 99% of counties in the U.S., with 87% of counties showing increases of >20%. Counties with the highest model-based suicide rates were consistently located across the western and northwestern U.S., with the exception of southern California and parts of Washington. Compared with more urban counties, more rural counties had the highest estimated suicide rates from 2005 to 2015, and also the largest increases over time.Conclusions: Mapping county-level suicide rates provides greater granularity in describing geographic patterns of suicide and contributes to a better understanding of changes in suicide rates over time. Findings may inform more targeted prevention efforts as well as future research on community-level risk and protective factors related to suicide mortality. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005- 2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and countyspecific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software RINLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation. Running head: Mapping Geographic Variation in Mortality Rates. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Reproductive health disparities may be partly explained by the cumulative effects of chronic stress experienced by socially disadvantaged groups. Although, telomere length (TL) and allostatic load score have each been used as biological markers of stress, the relationship between these two measures is unknown.Methods: We investigated the association between leucocyte TL and allostatic load score in 1503 non-pregnant women (20-44 years) participating in the National Health and Nutrition Examination Survey, 1999-2002. We constructed six different allostatic load scores using either quartile- or clinical-based cut-points for 14 biomarkers based on previously published methods. We estimated associations between TL and allostatic load scores and component biomarkers using linear regression, also assessing interactions by race/ethnicity.Results: After adjustment for age, longer TL was associated with higher HDL cholesterol and lower C-reactive protein and creatinine clearance; TL was not associated with the other component biomarkers. Shorter TL was associated with higher allostatic load scores for the two clinical cut-point-based scores after adjustment for age, but not the four scores based on quartile cut-points. Significant interactions by race/ethnicity were observed for TL and HbA1c and triglycerides, but not for other component biomarkers or allostatic load scores.Conclusions: Although TL and allostatic load score are both considered measures of cumulative stress, most component biomarkers and scores using quartile-based cut-points were not associated with TL. In reproductive-aged women, allostatic load scores using clinical-based cut-points were more strongly associated with TL compared with quartile-based scores. [ABSTRACT FROM AUTHOR]

We examined consumption of different types of infant formula (eg, cow’s milk, soy, gentle/lactose-reduced, and specialty) and regular milk among a nationally representative sample of 1864 infants, 0 to 12 months old, from the National Health and Nutrition Examination Survey, 2003-2010. Among the 81% of infants who were fed formula or regular milk, 69% consumed cow’s milk formula, 12% consumed soy formula, 5% consumed gentle/ lactose-reduced formulas, 6% consumed specialty formulas, and 13% consumed regular milk products. There were differences by household education and income in the percentage of infants consuming cow’s milk formula and regular milk products. The majority of infants in the United States who were fed formula or regular milk consumed cow’s milk formula (69%), with lower percentages receiving soy, specialty, gentle/sensitive, or lactose-free/reduced formulas. Contrary to national recommendations, 13% of infants younger than 1 year consumed regular milk, and the percentage varied by household education and income levels. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To describe the contribution of whole fruit, including discrete types of fruit, to total fruit consumption and to investigate differences in consumption by sociodemographic characteristics. METHODS: We analyzed data from 3129 youth aged 2 to 19 years from the National Health and Nutrition Examination Survey, 2011 to 2012. Using the Food Patterns Equivalents Database and the What We Eat in America 150 food groups, we calculated the contribution of whole fruit, 100% fruit juices, mixed fruit dishes, and 12 discrete fruit and fruit juices to total fruit consumption. We examined differences by age, gender, race and Hispanic origin, and poverty status. RESULTS: Nearly 90% of total fruit intake came from whole fruits (53%) and 100% fruit juices (34%) among youth aged 2 to 19 years. Apples, apple juice, citrus juice, and bananas were responsible for almost half of total fruit consumption. Apples accounted for 18.9% of fruit intake. Differences by age were predominately between youth aged 2 to 5 years and 6 to 11 years. For example, apples contributed a larger percentage of total fruit intake among youth 6 to 11 years old (22.4%) than among youth 2 to 5 years old (14.6%), but apple juice contributed a smaller percentage (8.8% vs 16.8%), P < .05. There were differences by race and Hispanic origin in intake of citrus fruits, berries, melons, dried fruit, and citrus juices and other fruit juices. CONCLUSIONS: These findings provide insight into what fruits US youth are consuming and sociodemographic factors that may influence consumption. [ABSTRACT FROM AUTHOR]

Objectives: Age-at-menopause and leukocyte telomere length (LTL) are both associated with biologic aging. Therefore, it would be reasonable to hypothesize that LTL may also serve as a marker for reproductive aging as shorter LTL may be associated with earlier age-at-menopause.Methods: We analyzed data from 799 post-menopausal (ages 41-85) participants in the National Health and Nutrition Examination Survey (1999-2002), a nationally representative sample of U.S. women.Results: Controlling for behavioral, socio-demographic, and health-related determinants of menopause, we found that among non-Hispanic white women, an increase of one standard deviation in LTL was associated with a 0.43 year higher reported age-at-menopause. Among Mexican-Americans, an increase of one standard deviation in LTL was associated with a 1.56 year earlier menopause. There was no significant association between LTL and age-at-menopause among non-Hispanic black women.Conclusions: Our main finding is evidence of a strong interaction by race/ethnicity in the association between LTL and age-at-menopause. This evidence does not support the hypothesis that shorter LTL is a predictor of earlier age-at-menopause, as the magnitude and direction of the associations between LTL and age-at-menopause varied across racial/ethnic groups. [ABSTRACT FROM AUTHOR]

ObjectiveTo describe the contribution of mixed dishes to vegetable consumption and to estimate vegetable intake according to specific types of vegetables and other foods among US children and adolescents.DesignThe 2003–2008 National Health and Nutrition Examination Survey (NHANES), a nationally representative probability survey conducted in the USA.SettingCivilian non-institutionalized US population.SubjectsAll children and adolescents aged 2–18 years who met eligibility criteria (n 9169).ResultsApproximately 59 % of total vegetable intake came from whole forms of vegetables with 41 % coming from a mixed dish. White potatoes (10·7 (se 0·6) %), fried potatoes (10·2 (se 0·4) %), potato chips (8·6 (se 0·5) %) and other vegetables (9·2 (se 0·5) %) accounted for most vegetables in their whole forms, whereas pasta dishes (9·5 (se 0·4) %), chilli/soups/stews (7·0 (se 0·5) %), pizza/calzones (7·6 (se 0·3) %) and other foods (13·7 (se 0·6) %) accounted for most mixed dishes. Usual mean vegetable intake was 1·02 cup equivalents/d; however, after excluding vegetables from mixed dishes, mean intake fell to 0·54 cup equivalents/d and to 0·32 cup equivalents/d when fried potatoes were further excluded.ConclusionsMixed dishes account for nearly half of overall vegetable intake in US children and adolescents. It is critical for future research to examine various components of vegetable intake carefully in order to inform policy and programmatic efforts aimed at improving dietary intake among children and adolescents. [ABSTRACT FROM AUTHOR]

Objectives. We sought to measure overall disparities in pregnancy outcome incorporating data from the many race and ethnic groups that compose the US population, to improve understanding of how disparities may have changed overtime. Methods. We used Birth Cohort Linked Birth-Infant Death Data Files from US Vital Statistics from 1989-1990 and 2005-2006 to examine multigroup indices of racial and ethnic disparities in the overall infant mortality rate (IMR) preterm birth rate, and gestational age-specific IMRs. We calculated selected absolute and relative multigroup disparity metrics weighting subgroups equally and by population size. Results. Overall IMR decreased on the absolute scale, but increased on the population-weighted relative scale. Disparities in the preterm birth rate decreased on both the absolute and relative scales, and across equally weighted and population-weighted indices. Disparities in preterm IMR increased on both the absolute and relative scales. Conclusions. Infant mortality is a common bellweather of general and maternal and child health. Despite significant decreases in disparities in the preterm birth rate, relative disparities in overall and preterm IMRs increased significantly over the past 20 years. [ABSTRACT FROM AUTHOR]

Over the past several years, the death rate associated with drug poisoning has increased by over 300% in the U.S. Drug poisoning mortality varies widely by state, but geographic variation at the substate level has largely not been explored. National mortality data (2007-2009) and small area estimation methods were used to predict age-adjusted death rates due to drug poisoning at the county level, which were then mapped in order to explore: whether drug poisoning mortality clusters by county, and where hot and cold spots occur (i.e., groups of counties that evidence extremely high or low age-adjusted death rates due to drug poisoning). Results highlight several regions of the U.S. where the burden of drug poisoning mortality is especially high. Findings may help inform efforts to address the growing problem of drug poisoning mortality by indicating where the epidemic is concentrated geographically. [ABSTRACT FROM AUTHOR]

Abstract: Over the past several years, the death rate associated with drug poisoning has increased by over 300% in the U.S. Drug poisoning mortality varies widely by state, but geographic variation at the substate level has largely not been explored. National mortality data (2007–2009) and small area estimation methods were used to predict age-adjusted death rates due to drug poisoning at the county level, which were then mapped in order to explore: whether drug poisoning mortality clusters by county, and where hot and cold spots occur (i.e., groups of counties that evidence extremely high or low age-adjusted death rates due to drug poisoning). Results highlight several regions of the U.S. where the burden of drug poisoning mortality is especially high. Findings may help inform efforts to address the growing problem of drug poisoning mortality by indicating where the epidemic is concentrated geographically. [Copyright &y& Elsevier]

BACKGROUND AND OBJECTIVE: Physicians and policy makers are increasingly interested in caffeine intake among children and adolescents in the advent of increasing energy drink sales. However, there have been no recent descriptions of caffeine or energy drink intake in the United States. We aimed to describe trends in caffeine intake over the past decade among US children and adolescents. METHODS: We assessed trends and demographic differences in mean caffeine intake among children and adolescents by using the 24-hour dietary recall data from the 1999-2010 NHANES. In addition, we described the proportion of caffeine consumption attributable to different beverages, including soda, energy drinks, and tea. RESULTS: Approximately 73% of children consumed caffeine on a given day. From 1999 to 2010, there were no significant trends in mean caffeine intake overall; however, caffeine intake decreased among 2- to 11-year-olds (P < .01) and Mexican-American children (P = .003). Soda accounted for the majority of caffeine intake, but this contribution declined from 62% to 38% (P < .001). Coffee accounted for 10% of caffeine intake in 1999-2000 but increased to nearly 24% of intake in 2009-2010 {P < .001). Energy drinks did not exist in 1999-2000 but increased to nearly 6% of caffeine intake in 2009-2010. CONCLUSIONS: Mean caffeine intake has not increased among children and adolescents in recent years. However, coffee and energy drinks represent a greater proportion of caffeine intake as soda intake has declined. These findings provide a baseline for caffeine intake among US children and young adults during a period of increasing energy drink use. [ABSTRACT FROM AUTHOR]

The article presents an update on the number of excess deaths linked to the COVID-19 pandemic in the U.S. from January 2020 to February 2021 as per the Center for Disease Control and Prevention's (CDC) National Center for Health Statistics (NCHS). The NCHS used data from the National Vital Statistics System (NVSS) in determining excess death figures. Also cited are the limitations of the study like the possible underestimation of deaths due to reporting lags.

This study examined food availability along children's paths to and from elementary school, and associations with change in body mass index (BMI) and waist circumference over 1 year. Secondary data from 319 children aged 8-13 years from the 'Multiple Opportunities to Reach Excellence' Project was used. Child anthropometry and demographic variables were obtained at baseline (2007) and 1 year follow-up. Food outlet locations ( n = 1,410) were obtained from the Baltimore City Health Department and validated by ground-truthing. Secondary data on healthy food availability within select food stores in Baltimore City in 2007 were obtained via a validated food environment assessment measure, the Nutrition Environments Measures Study. Multilevel models were used to examine associations between availability of healthy food and number of various food outlets along paths to school and child anthropometric change over 1 year. Controlling for individual-, neighborhood-, and school-level characteristics, results indicated that higher healthy food availability within a 100 m buffer of paths to school was associated with 0.15 kg/m lower BMI gain ( p = 0.015) and 0.47 cm smaller waist circumference gain ( p = 0.037) over 1 year. Although prior research has illuminated the importance of healthy food choices within school and home environments, the current study suggests that exposure to the food environment along paths to school should be further explored in relation to child health outcomes. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: Although eliminating health disparities by race, ethnicity, and socioeconomic status (SES) is a top public health priority internationally and in the United States, weight-related racial/ethnic and SES disparities persist among adults and children in the United States. Few studies have examined how these disparities have changed over time; these studies are limited by the reliance on rate differences or ratios to measure disparities. We sought to advance existing research by using a set of disparity metrics on both the absolute and relative scales to examine trends in childhood obesity disparities over time. Methods: Data from 7066 children, ages 2 to 18 years, in the National Health and Nutrition Examination Surveys were used to explore trends in racial/ethnic and SES disparities in pediatric obesity from 2001 to 2010 using a set of different disparity metrics. Results: Racial/ethnic and SES-related disparities in pediatric obesity did not change significantly from 2001 to 2010 and remain significant. Conclusions: Disparities in obesity have not improved during the past decade. The use of different disparity metrics may lead to different conclusions with respect to how disparities have changed over time, highlighting the need to evaluate disparities using a variety of metrics. [Copyright &y& Elsevier]

Abstract: Obtaining valid and accurate data on community food environments is critical for research evaluating associations between the food environment and health outcomes. This study utilized ground-truthing and remote-sensing technology to validate a food outlet retail list obtained from an urban local health department in Baltimore, Maryland in 2009. Ten percent of outlets (n=169) were assessed, and differences in accuracy were explored by neighborhood characteristics (96 census tracts) to determine if discrepancies were differential or non-differential. Inaccuracies were largely unrelated to a variety of neighborhood-level variables, with the exception of number of vacant housing units. Although remote-sensing technologies are a promising low-cost alternative to direct observation, this study demonstrated only moderate levels of agreement with ground-truthing. [Copyright &y& Elsevier]

In the U.S. Army, motor vehicle crashes (MVCs), both privately owned and military, are a leading cause of injury and death. Few studies have described the distribution and trends of MVCs among Army personnel, which may have been impacted by current military missions. This descriptive study of risk factors and select outcomes is from safety report data maintained by the U.S. Army Combat Readiness/Safety Center on 11,469 active duty Army personnel involved in MVCs, 1999-2006. The majority (66%) of Soldiers in MVCs were in military vehicles within the continental United States (68%). The average age of individuals involved in MVCs was 27.7 years old. Males had a consistently higher MVC rate than females. The average cost per MVC related to property damage and injuries was $36,039 and $24,038, respectively. Results suggest a need for additional exploration of MVCs involving Army vehicles, which were the most common and among the most costly. [ABSTRACT FROM AUTHOR]

Mortality surveillance systems can have limitations, including reporting delays, incomplete reporting, missing data, and insufficient detail on important risk or sociodemographic factors that can impact the accuracy of estimates of current trends, disease severity, and related disparities across subpopulations. The Centers for Disease Control and Prevention used multiple data systems during the COVID-19 emergency response—line-level case‒death surveillance, aggregate death surveillance, and the National Vital Statistics System—to collectively provide more comprehensive and timely information on COVID-19‒associated mortality necessary for informed decisions. This article will review in detail the line-level, aggregate, and National Vital Statistics System surveillance systems and the purpose and use of each. This retrospective review of the hybrid surveillance systems strategy may serve as an example for adaptive informational approaches needed over the course of future public health emergencies. (Am J Public Health. 2024;114(10):1071–1080. https://doi.org/10.2105/AJPH.2024.307743) [ABSTRACT FROM AUTHOR]

The article discusses the recommendations of the American Academy of Pediatrics for minimum daily intake of vitamin D for infants and children in the U.S. Topics discussed include increased risk of vitamin D deficiency in breastfed infants, specific reference of the National Health and Nutrition Examination Survey for analysis of dietary recall information of infants and persistent incidence of rickets due to vitamin D deficiency.

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. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the association between pregnancy loss history and adverse pregnancy outcomes.Methods: Pregnancy history was captured during a computer-assisted personal interview for 21,277 women surveyed in the National Survey of Family Growth (1995-2013). History of pregnancy loss (<20 weeks) at first parity was categorized in three ways: number of losses, maximum gestational age of loss(es), and recency of last pregnancy loss. We estimated risk ratios for a composite measure of selected adverse pregnancy outcomes (preterm, stillbirth, or low birthweight) at first parity and in any future pregnancy, separately, using predicted margins from adjusted logistic regression models.Results: At first parity, compared with having no loss, having 3+ previous pregnancy losses (adjusted risk ratio (aRR) = 1.66 [95% CI = 1.13, 2.43]), a maximum gestational age of loss(es) at ≥10 weeks (aRR = 1.28 [1.04, 1.56]) or having experienced a loss 24+ months ago (aRR = 1.36 [1.10, 1.68]) were associated with increased risks of adverse pregnancy outcomes. For future pregnancies, only having a history of 3+ previous pregnancy losses at first parity was associated with increased risks (aRR = 1.97 [1.08, 3.60]).Conclusion: Number, gestational age, and recency of pregnancy loss at first parity were associated with adverse pregnancy outcomes in U.S. women. [ABSTRACT FROM AUTHOR]

Purpose: To explore whether contextual variables attenuate disparities in weight among 18,639 US children and adolescents aged 2 to 18 years participating in the National Health and Nutrition Examination Survey, 2001 to 2010.Methods: Disparities were assessed using the Symmetrized Rényi Index, a new measure that summarizes disparities in the severity of a disease, as well as the prevalence, across multiple population groups. Propensity score subclassification was used to ensure covariate balance between racial and ethnic subgroups and account for individual-level and contextual covariates.Results: Before propensity score subclassification, significant disparities were evident in the prevalence of overweight and/or obesity and the degree of excess weight among overweight/obese children and adolescents. After propensity score subclassification, racial/ethnic disparities in the prevalence and severity of excess weight were completely attenuated within matched groups, indicating that racial and ethnic differences were explained by social determinants such as neighborhood socioeconomic and demographic factors.Conclusions: The limited overlap in covariate distributions between various racial/ethnic subgroups warrants further attention in disparities research. The attenuation of disparities within matched groups suggests that social determinants such as neighborhood socioeconomic factors may engender disparities in weight among US children and adolescents. [ABSTRACT FROM AUTHOR]

Background: Drug poisoning mortality has increased substantially in the U.S. over the past 3 decades. Previous studies have described state-level variation and urban-rural differences in drug-poisoning deaths, but variation at the county level has largely not been explored in part because crude county-level death rates are often highly unstable.Purpose: The goal of the study was to use small-area estimation techniques to produce stable county-level estimates of age-adjusted death rates (AADR) associated with drug poisoning for the U.S., 1999-2009, in order to examine geographic and temporal variation.Methods: Population-based observational study using data on 304,087 drug-poisoning deaths in the U.S. from the 1999-2009 National Vital Statistics Multiple Cause of Death Files (analyzed in 2012). Because of the zero-inflated and right-skewed distribution of drug-poisoning death rates, a two-stage modeling procedure was used in which the first stage modeled the probability of observing a death for a given county and year, and the second stage modeled the log-transformed drug-poisoning death rate given that a death occurred. Empirical Bayes estimates of county-level drug-poisoning death rates were mapped to explore temporal and geographic variation.Results: Only 3% of counties had drug-poisoning AADRs greater than ten per 100,000 per year in 1999-2000, compared to 54% in 2008-2009. Drug-poisoning AADRs grew by 394% in rural areas compared to 279% for large central metropolitan counties, but the highest drug-poisoning AADRs were observed in central metropolitan areas from 1999 to 2009.Conclusions: There was substantial geographic variation in drug-poisoning mortality across the U.S. [ABSTRACT FROM AUTHOR]

Background: Drug poisoning mortality has increased substantially in the U.S. over the past 3 decades. Previous studies have described state-level variation and urban–rural differences in drug-poisoning deaths, but variation at the county level has largely not been explored in part because crude county-level death rates are often highly unstable. Purpose: The goal of the study was to use small-area estimation techniques to produce stable county-level estimates of age-adjusted death rates (AADR) associated with drug poisoning for the U.S., 1999–2009, in order to examine geographic and temporal variation. Methods: Population-based observational study using data on 304,087 drug-poisoning deaths in the U.S. from the 1999–2009 National Vital Statistics Multiple Cause of Death Files (analyzed in 2012). Because of the zero-inflated and right-skewed distribution of drug-poisoning death rates, a two-stage modeling procedure was used in which the first stage modeled the probability of observing a death for a given county and year, and the second stage modeled the log-transformed drug-poisoning death rate given that a death occurred. Empirical Bayes estimates of county-level drug-poisoning death rates were mapped to explore temporal and geographic variation. Results: Only 3% of counties had drug-poisoning AADRs greater than ten per 100,000 per year in 1999–2000, compared to 54% in 2008–2009. Drug-poisoning AADRs grew by 394% in rural areas compared to 279% for large central metropolitan counties, but the highest drug-poisoning AADRs were observed in central metropolitan areas from 1999 to 2009. Conclusions: There was substantial geographic variation in drug-poisoning mortality across the U.S. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

Background Coronavirus disease 2019 (COVID-19)–associated fungal infections cause severe illness, but comprehensive data on disease burden are lacking. We analyzed US National Vital Statistics System (NVSS) data to characterize disease burden, temporal trends, and demographic characteristics of persons dying of fungal infections during the COVID-19 pandemic. Methods Using NVSS's January 2018–December 2021 Multiple Cause of Death Database, we examined numbers and age-adjusted rates (per 100 000 population) of deaths due to fungal infection by fungal pathogen, COVID-19 association, demographic characteristics, and year. Results Numbers and age-adjusted rates of deaths due to fungal infection increased from 2019 (n = 4833; rate, 1.2 [95% confidence interval, 1.2–1.3]) to 2021 (n = 7199; rate, 1.8 [1.8–1.8] per 100 000); of 13 121 such deaths during 2020–2021, 2868 (21.9%) were COVID-19 associated. Compared with non–COVID-19–associated deaths (n = 10 253), COVID-19–associated deaths more frequently involved Candida (n = 776 [27.1%] vs n = 2432 [23.7%], respectively) and Aspergillus (n = 668 [23.3%] vs n = 1486 [14.5%]) and less frequently involved other specific fungal pathogens. Rates of death due to fungal infection were generally highest in nonwhite and non-Asian populations. Death rates from Aspergillus infections were approximately 2 times higher in the Pacific US census division compared with most other divisions. Conclusions Deaths from fungal infection increased during 2020–2021 compared with previous years, primarily driven by COVID-19–associated deaths, particularly those involving Aspergillus and Candida. Our findings may inform efforts to prevent, identify, and treat severe fungal infections in patients with COVID-19, especially in certain racial/ethnic groups and geographic areas. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 thatwere 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 geometricmean BLLs and the prevalence of BLLs of 3micrograms per deciliter or higheramongchildrenwhowerelivingin assisted housing at the time of theirNHANESblood 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 mg/dL; 95% confidence interval [CI] = 1.31, 1.57) than comparable children who did not receive housing assistance (1.79 mg/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. [ABSTRACT FROM AUTHOR]

Purpose: Although eliminating health disparities by race, ethnicity, and socioeconomic status (SES) is a top public health priority internationally and in the United States, weight-related racial/ethnic and SES disparities persist among adults and children in the United States. Few studies have examined how these disparities have changed over time; these studies are limited by the reliance on rate differences or ratios to measure disparities. We sought to advance existing research by using a set of disparity metrics on both the absolute and relative scales to examine trends in childhood obesity disparities over time.Methods: Data from 7066 children, ages 2 to 18 years, in the National Health and Nutrition Examination Surveys were used to explore trends in racial/ethnic and SES disparities in pediatric obesity from 2001 to 2010 using a set of different disparity metrics.Results: Racial/ethnic and SES-related disparities in pediatric obesity did not change significantly from 2001 to 2010 and remain significant.Conclusions: Disparities in obesity have not improved during the past decade. The use of different disparity metrics may lead to different conclusions with respect to how disparities have changed over time, highlighting the need to evaluate disparities using a variety of metrics. [ABSTRACT FROM AUTHOR]

The National Center for Health Statistics' (NCHS's) National Vital Statistics System (NVSS) collects, processes, codes, and reviews death certificate data and disseminates the data in annual data files and reports. With the global rise of COVID-19 in early 2020, the NCHS mobilized to rapidly respond to the growing need for reliable, accurate, and complete real-time data on COVID-19 deaths. Within weeks of the first reported US cases, NCHS developed certification guidance, adjusted internal data processing systems, and stood up a surveillance system to release daily updates of COVID-19 deaths to track the impact of the COVID-19 pandemic on US mortality. This report describes the processes that NCHS took to produce timely mortality data in response to the COVID-19 pandemic. (Am J Public Health. 2021;111(12):2133–2140. https://doi.org/10.2105/AJPH.2021.306519) [ABSTRACT FROM AUTHOR]

The article reports on a study that examined rural and urban progress toward national targets for rates of seven major causes of death tracked by Healthy People 2020 initiative. Highlights include the use of data from the National Vital Statistics System to assess age-adjusted death rates for the major causes of death in urban and rural areas, variation in target attainment for other causes of death by rurality and region, and a decline in diabetes-related rates in rural areas in the Northeast.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]