National Center For Health Statistics Research Articles

Cancer statistics, 2024.

Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes using incidence data collected by central cancer registries (through 2020) and mortality data collected by the National Center for Health Statistics (through 2021). In 2024, 2,001,140 new cancer cases and 611,720 cancer deaths are projected to occur in the United States. Cancer mortality continued to decline through 2021, averting over 4 million deaths since 1991 because of reductions in smoking, earlier detection for some cancers, and improved treatment options in both the adjuvant and metastatic settings. However, these gains are threatened by increasing incidence for 6 of the top 10 cancers. Incidence rates increased during 2015-2019 by 0.6%-1% annually for breast, pancreas, and uterine corpus cancers and by 2%-3% annually for prostate, liver (female), kidney, and human papillomavirus-associated oral cancers and for melanoma. Incidence rates also increased by 1%-2% annually for cervical (ages 30-44 years) and colorectal cancers (ages <55 years) in young adults. Colorectal cancer was the fourth-leading cause of cancer death in both men and women younger than 50years in the late-1990s but is now first in men and second in women. Progress is also hampered by wide persistent cancer disparities; compared to White people, mortality rates are two-fold higher for prostate, stomach and uterine corpus cancers in Black people and for liver, stomach, and kidney cancers in Native American people. Continued national progress will require increased investment in cancer prevention and access to equitable treatment, especially among American Indian and Alaska Native and Black individuals.

Endogenous and Exogenous Opioids: Role in Substance Use Disorders.

Opioid use disorders have become an epidemic in recent years with rates nearly quadrupling since 1999 according to the US Centers for Disease Control and Prevention (Centers for Disease Control, Wide-ranging online data for epidemiologic research (WONDER). CDC, National Center for Health Statistics, Atlanta. Retrieved December 19, 2017, from http://wonder.cdc.gov, 2016). To understand substance use disorder (SUD) as a disease, many aspects must be studied including the circuitry in the brain, adaptations to neuronal circuitry and neurotransmitters, genetic variations increasing the risk for SUD, and treatments available for SUD. The mechanism in which an exogenous opioid may cause SUD is nearly identical to the mechanism of an endogenous opioid. This chapter reviews the clinical and epidemiological aspects of opioid use disorder, as well as the interactions between endogenous and exogenous opioids. Additionally, this chapter discusses current scientific data regarding genetic variations and mechanisms within brain circuitry and the role of endogenous opioids in substance use disorders generally (and opioid use disorder specifically). Future applications of these data to treatment of substance use disorders are also discussed.

The causal effect of adipose tissue on Hodgkin's lymphoma: two-sample Mendelian randomization study and validation.

Extensive research has been conducted on the correlation between adipose tissue and the risk of malignant lymphoma. Despite numerous observational studies exploring this connection, uncertainty remains regarding a causal relationship between adipose tissue and malignant lymphoma. The increase or decrease in adipose tissue was represented by the height of BMI. The BMI and malignant lymphoma genome-wide association studies (GWAS) used a summary dataset from the OPEN GWAS website. Single-nucleotide polymorphisms (SNPs) that met the criteria of P <5e-8 and LD of r2=0.001 in the BMI GWAS were chosen as genetic instrumental variants (IVs). Proxy SNPs with LD of r2 > 0.8 were identified, while palindromic and outlier SNPs were excluded. Mendelian randomization (MR) analysis used five methods, including inverse-variance weighted (IVW) model, weighted median (WM), MR-Egger, simple mode, and weighted mode. Sensitivity assessments included Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis. Participants randomly selected by the National Center for Health Statistics (NHANSE) and newly diagnosed HL patients at Fujian Medical University Union Hospital were used for external validation. The results of the MR analysis strongly supported the causal link between BMI and Hodgkin's lymphoma (HL). The research demonstrated that individuals with lower BMI face a significantly increased risk of developing HL, with a 91.65% higher risk (ORIVW = 0.0835, 95% CI 0.0147 - 0.4733, P = 0.005). No signs of horizontal or directional pleiotropy were observed in the MR studies. The validation results aligned with the results from the MR analysis (OR = 0.871, 95% CI 0.826 - 0.918, P< 0.001). And there was no causal relationship between BMI and non-Hodgkin's lymphoma (NHL). The MR analysis study demonstrated a direct correlation between lower BMI and HL. This suggested that a decrease in adipose tissue increases the risk of developing HL. Nevertheless, further research is essential to grasp the underlying mechanism of this causal association comprehensively.

Predictive value of hepatitis B serological indicators for mortality among cancer survivors and validation in a gastric cancer cohort.

Hepatitis B virus (HBV) infection has gradually been considered to associate with cancer development and progression. This study aimed to explore the associations of serological indicators of HBV infection with mortality risk among cancer survivors and further validated using a gastric cancer (GC) cohort from China, where HBV infection is endemic. National Center for Health Statistics' National Health and Nutrition Examination Survey (NHANES) data were used in this study. Individuals with positive results of hepatitis B core antigen (anti-HBc) were considered to have current or past HBV infection. Serological indicators were positive only for hepatitis B surface antibodies (anti-HBs), indicating vaccine-induced immunity, whereas negativity for all serologic indicators was considered to indicate the absence of HBV infection and immunity to HBV. The GC cohort included patients from the First Hospital of Jilin University, China. The median follow-up time of the NHANES was 10 years; during the follow-up, 1505 deaths occurred. The results revealed that anti-HBs-positive cancer survivors had a 39% reduced risk of mortality (hazard ratio [HR] 0.61, 95% confidence interval [CI] 0.44-0.85). Men and individuals aged <65 years old with past exposure to HBV had higher mortality risk (HR 1.52, 95% CI 1.09-2.13; HR 2.07, 95% CI 1.13-3.83). In this GC cohort, individuals who were only anti-HBs-positive showed a reduced risk of mortality (HR 0.77, 95% CI 0.62-0.95). Thus, anti-HBs positivity was a significant factor of decreased mortality among cancer survivors. More rigorous surveillance is necessary for cancer survivors with anti-HBc positivity, particularly men, and younger individuals.

NURSING HOME INVESTMENT IN HEALTH INFORMATION TECHNOLOGY – AN ORGANIZATIONAL SLACK PERSPECTIVE

Abstract Organizational slack refers to excess resources (e.g., financial, social capital, human capital) an organization accumulates to adapt to changing internal and external contexts. Nursing homes operate in a severely resource-constrained environment, and therefore have limited ability to accumulate organizational slack. However, nursing homes that do accumulate slack may be more likely to invest in health information technology (HIT). To test this, we examine associations between organizational slack and HIT maturity. HIT maturity is the level of IT capabilities, extent of use, and integration in resident care, clinical support, and administration. We linked 2018 data from a national nursing home HIT maturity survey (N=525) to nursing home characteristics from LTCfocus.org, CMS data, National Center for Health Statistics, Medicare cost reports, and other county-level statistics. We incorporated Simple Linear Regression, controlling for facility-level sex, race, case-mix, and urban/rural location. Average 3-year operating income for Stage 0 nursing homes was -$4,387 per bed (n=7) compared to $42,768 per bed in Stage 6 nursing homes (n=17). Higher HIT maturity was associated with greater percentages of Medicare patients and shorter distances to the closest hospital. Our regression model also demonstrated significant associations with operating income per bed, chain affiliation, total beds, occupancy percentage, moderately concentrated counties and case-mix adjusted staffing. In this sample, larger, more financially stable organizations (i.e., those with more slack) may be able to invest more in HIT. As HIT maturity has been shown to be associated with improved patient outcomes, disparities may widen in organizations with lower levels of slack.

IDENTIFYING THE RELATIONSHIP BETWEEN ALZHEIMER’S DISEASE PREVALENCE AND CURRENT SERVICE USE IN OHIO’S 88 COUNTIES

Abstract Recently released data reveals that over 235,000 people over the age of 65 have Alzheimer’s disease and related dementia (ADRD) in Ohio. Using 2020 data from the National Center for Health Statistics, county-level specific ADRD prevalence estimates for Ohio’s 88 counties were also prepared (Range: 9.4-13.4 per 1000 individuals 65+). Researchers, practitioners, and policy-makers can use these estimates to better understand the reach and impact of ADRD in local communities. Nationally and in Ohio, care and support for older adults and specifically older adults with ADRD typically falls to family caregivers, home- and community-based service (HCBS) providers, and residential care providers such as nursing homes. This study pairs the county-level ADRD prevalence data with county-level data on available services (e.g., Memory Care Units, nursing home beds) and service users (e.g., HCBS users). The 10 counties in Ohio with the highest prevalence rates are home to nearly 60% of the 65+ population statewide. Additionally, these counties had a significantly higher proportion of older Black/Hispanic individuals than the other counties (10.8 versus 2.9). When looking at capacity, the top 10 counties contained just 12% of all nursing home beds, but 54% of nursing homes memory care units for the entire state. When considering service use, these 10 counties served a smaller percentage of the state’s HCBS users (13%). For Ohio and other states, it is important to explore available services and current service usage when faced with the increasing estimates of people living with ADRD.

U.S. stillbirth surveillance: The national fetal death file and other data sources

The National Vital Statistics System is the primary source of information on fetal deaths of 20 weeks of gestation or more in the United States. Data are cooperatively produced by jurisdiction vital statistics offices and the National Center for Health Statistics. In order to promote the uniformity of data, the National Center for Health Statistics issues The Model State Vital Statistics Act and Regulations, and produces standard certificates and reports, developed in collaboration with the states, to inform the development of jurisdictional vital records laws and regulations and data collection. While there are challenges in collecting national fetal death data, there are ongoing data quality improvement efforts to address them. Improved national fetal death data and data from other sources will continue to add insights into the risks, causes and prevention of fetal death.

Multiple imputation of missing data with skip-pattern covariates: a comparison of alternative strategies

Multiple imputation (MI) is a widely used approach to address missing data issues in surveys. Variables included in MI can have various distributional forms with different degrees of missingness. However, when variables with missing data contain skip patterns (i.e. questions not applicable to some survey participants are thus skipped), implementation of MI may not be straightforward. In this research, we compare two approaches for MI when skip-pattern covariates with missing values exist. One approach imputes missing values in the skip-pattern variables only among applicable subjects (denoted as imputation among applicable cases (IAAC)). The second approach imputes skip-pattern covariates among all subjects while using different recoding methods on the skip-pattern variables (denoted as imputation with recoded non-applicable cases (IWRNC)). A simulation study is conducted to compare these methods. Both approaches are applied to the 2015 and 2016 Research and Development Survey data from the National Center for Health Statistics.

Native American “deaths of despair” and economic conditions

“Deaths of despair” – deaths caused by suicide, drug use, and alcohol use – have increased among non-Hispanic whites who do not have a college degree. We analyze confidential-use data from the National Center for Health Statistics that contains death certificates from 2005 to 2017 (total of 21,177,490 records) linked with measures of local labor market activity. We show that deaths of despair are proportionally larger among Native Americans than non-Hispanic white Americans and that economic conditions have a different relationship with deaths of despair among Native Americans than for non-Hispanic white Americans. Improvements in economic conditions are associated with decreased deaths from drug use, alcohol use, and suicide for non-Hispanic white Americans. On the other hand, in counties with higher labor force participation rates, lower unemployment, and higher ratios of employees to residents, there are significantly higher proportions of Native American deaths attributed to alcohol and drug use.

The Relationship Between Anthropometric Z-Score Measurements and Ocular Structures in Turkish Children.

Objective (Aim): This study explores the contact between anthropometric Z-score values and ocular parameters in children. Recent studies investigated the relationship, and contact between anthropometric measurements and ocular parameters in children, and height, weight, body mass index, and percentile curves are mostly used as anthropometric data. However, today, different scoring systems such as "Z-score" classify anthropometric values. Methods: Height and body mass index Z-scores were calculated for 725 children. Biometric and refractive measurements of all children were noted. For different reference values, those with a Z-score below the negative value of the reference were defined as a low Z-score, those between the negative and positive value of the reference were defined as a normal Z-score, those with a Z-score greater than the positive value of the reference were defined as a high Z-score. The mean ocular measurement results in the low, normal, and high Z-score groups were compared, and they were pointed to reach the reference value in both negative and positive sides which created the foremost critical contrast between the groups. Results: For a value of "-1" and "+1.5" in the height Z-score, from low to normal and from there to high Z-score group, axial length, and average corneal radius increased, and average corneal power decreased significantly. Anterior chamber depth increased from normal to high Z-score group, but no critical distinction was made between low and normal Z-score groups. Moreover, no critical distinction was observed in spherical equivalent refraction, central corneal thickness for height, and all values of body mass index. Conclusion: Considering a Z-score value of "-1" and "+1.5" as a reference value in children and anticipating the changes that may happen in the ocular structures of children at both ends of the Z-score, it may be useful to understand the effect of body development on ocular development more. Abbreviations: AL = Axial Length, ACD = Anterior Chamber Depth, BMI = Body Mass Index, NCHS = The United States National Center for Health Statistics, WHO = World Health Organization, NFHS 2 = National Family Health Survey 2, SER = Spherical Equivalent Refraction, CR = Average Corneal Radius, CP = Average Corneal Power, CCT = Central Corneal Thickness, HFAsZ = Height for Age Z-Score, BMIsZ = BMI for Age Z-Score, L = Low Z-score, N = Normal Z-score, H = High Z-score.

US County–Level Variation in Preterm Birth Rates, 2007-2019

Preterm birth is a leading cause of preventable neonatal morbidity and mortality. Preterm birth rates at the national level may mask important geographic variation in rates and trends at the county level. To estimate age-standardized preterm birth rates by US county from 2007 to 2019. This serial cross-sectional study used data from the National Center for Health Statistics composed of all live births in the US between 2007 and 2019. Data analyses were performed between March 22, 2022, and September 29, 2022. Age-standardized preterm birth (<37 weeks' gestation) and secondarily early preterm birth (<34 weeks' gestation) rates by county and year calculated with a validated small area estimation model (hierarchical bayesian spatiotemporal model) and percent change in preterm birth rates using log-linear regression models. Between 2007 and 2019, there were 51 044 482 live births in 2383 counties. In 2007, the national age-standardized preterm birth rate was 12.6 (95% CI, 12.6-12.7) per 100 live births. Preterm birth rates varied significantly among counties, with an absolute difference between the 90th and 10th percentile counties of 6.4 (95% CI, 6.2-6.7). The gap between the highest and lowest counties for preterm births was 20.7 per 100 live births in 2007. Several counties in the Southeast consistently had the highest preterm birth rates compared with counties in California and New England, which had the lowest preterm birth rates. Although there was no statistically significant change in preterm birth rates between 2007 and 2019 at the national level (percent change, -5.0%; 95% CI, -10.7% to 0.9%), increases occurred in 15.4% (95% CI, 14.1%-16.9%) of counties. The absolute and relative geographic inequalities were similar across all maternal age groups. Higher quartile of the Social Vulnerability Index was associated with higher preterm birth rates (quartile 4 vs quartile 1 risk ratio, 1.34; 95% CI, 1.31-1.36), which persisted across the study period. Similar patterns were observed for early preterm birth rates. In this serial cross-sectional study of county-level preterm and early preterm birth rates, substantial geographic disparities were observed, which were associated with place-based social disadvantage. Stability in aggregated rates of preterm birth at the national level masked increases in nearly 1 in 6 counties between 2007 and 2019.

The Connection Between the Occurrence of Infection and Cardiovascular Mortality

Infections have long been known to be connected with cardiovascular disease (CVD). There is research that indicates that some infections can directly affect the heart. However, we wanted to find out if the occurrence of infection is connected to CVD mortality.We analyzed data on adults (≥ 20 years) from the 1999–2010 National Health and Nutrition Examination Survey, which is a population-based survey conducted by the National Center for Health Statistics, with mortality data obtained through December 2019. We defined current infection as positive for various respiratory infections (head cold, chest cold, flu, pneumonia, ear infection) through self-reported data. Complex Samples Cox regression was used to determine the relationship of current infection occurrence and CVD-related mortality.Data was available for 880 adults in the United States population. The percentage of individuals who experienced mortality after current infection was higher than those who did not have current infection. The overall unadjusted hazard ratio for current infection to no current infection was 3.38 (2.49-4.59, p < 0.01). The age- and sex-adjusted HR remained strong at 2.81 (CI 0.78-10.18, p = 0.11) among adults after the results were controlled for medical (depression, obesity, C-reactive Protein) and demographic (poverty-income-ratio, ethnicity, gender, age) risk factors.There is a significant relationship between the occurrence of current infection and CVD mortality among all adults. Consequently, individuals with infection need better access to treating infections through services and overall healthcare. Health care professionals should be made aware of gaps in prevention of cardiovascular disease.

Rheumatoid Arthritis and the Connection with Cardiovascular Disease Mortality

Rheumatoid Arthritis is the most common type of autoimmune diseases. While the prognosis is known for these patients, it is unknown precisely how rheumatoid arthritis (RA) relates to cardiovascular (CVD) mortality.We analyzed data on adults (≥ 20 years) from the 1999–2010 National Health and Nutrition Examination Survey, which is a population-based survey conducted by the National Center for Health Statistics, with mortality data obtained through December 2019. We assessed for Rheumatoid Arthritis through self-reported data. Due to the complex sampling design, sample weights were utilized in order to analyze the data. Comparisons were analyzed using Pearson's Chi Square, simple, and multivariable Cox regression to determine the relationship of rheumatoid arthritis and CVD-related mortality. All missing variables were excluded.Data was available for 13,131 adults in the United States population. The percentage of individuals who experienced mortality after RA 38.5% (32.8-44.2) was higher than those who did not have RA (14.8% (13.8-15.8)). The overall unadjusted hazard ratio for RA to no RA was 3.38 (2.49-4.59, p < 0.01). The adjusted HR remained strong at 1.51 (CI 1.14-2.01, p < 0.01) among adults after the results were controlled for medical (obesity) and demographic (ethnicity, gender, age) risk factors.There is a significant relationship between RA and CVD mortality among all adults. Consequently, individuals with rheumatoid arthritis need better access to treat RA through services and overall healthcare. Health care professionals should be made aware of gaps in prevention of cardiovascular disease.

Association Between the Occurrence of Stroke and Overall Mortality

Stroke is an acute type of cerebrovascular disease. While it is known that strokes lead to cardiovascular mortality. However, very little is known about if occurrence of stroke is connected to overall mortality.We analyzed data on adults (≥ 20 years) from the 1999–2010 National Health and Nutrition Examination Survey, which is a population-based survey conducted by the National Center for Health Statistics, with mortality data obtained through December 2019. We assessed for stroke through self-reported data. Due to the complex sampling design, sample weights were utilized in order to analyze the data. Comparisons were analyzed using Pearson's Chi Square, simple, and multivariable Cox regression to determine the relationship of depression and cancer-related mortality. All missing variables were excluded.Data was available for 14,504 adults in the United States population. The percentage of individuals who experienced mortality after stroke was higher among African American population 1.5% (1.21-1.73) than the Hispanic population 0.55% (0.42-0.74). The overall unadjusted hazard ratio for stroke to no stroke was 6.16 (5.32-7.13, p < 0.01). The adjusted HR remained strong at 1.97 (CI 1.74-2.24, p < 0.01) among adults after the results were controlled for medical (obesity) and demographic (gender, age, poverty-income-ratio) risk factors.There is a significant relationship between stroke occurrence and overall mortality among all adults. Consequently, individuals with stroke need better access to prevent this disease through services and overall healthcare. Health care professionals should be made aware of gaps in prevention of stroke.

Addressing State-Based Differences in Suicide Fatalities Among Children and Adolescents—Finding Another Way

This Viewpoint uses state-based data obtained from the National Center for Health Statistics’ Web-Based Injury Statistics Query and Reporting System to discuss the importance of legislatively addressing firearm-related suicide fatalities among children and adolescents in the US.

Prevalence of Alzheimer’s dementia in the 50 U.S. states and 3142 counties: A population estimate using the 2020 bridged‐race postcensal from the National Center for Health Statistics

AbstractBackgroundEstimating the prevalence and number of people with Alzheimer’s dementia in 50 U.S. states and 3142 counties can provide a better understanding of region‐specific disease burden.MethodWe utilized cognitive data from the Chicago Health and Aging Project (CHAP), a population‐based study, and combined it with the National Center for Health Statistics (NHCS) 2020 bridged‐race population estimates and determined the state‐ and county‐specific prevalence of Alzheimer’s dementia for adults 65 years and older.ResultA higher prevalence of Alzheimer’s dementia was estimated in the East and Southeastern regions of the U.S., with the highest in Maryland (12.9%), New York (12.7%), Mississippi (12.5%), and Florida (12.5%). California and Illinois were also among the 10 states with a higher prevalence of Alzheimer’s. U.S. states. California had the highest number of people with Alzheimer’s dementia, with 719.7 (95%CI 665.0, 774.4) thousand, Texas with 579.9 (95%CI 539.9, 620.0) thousand, and Florida with 459.3 (95%CI 422.7, 496.0) thousand. The top 3 counties with the highest prevalence, 16.6%, respectively, were Miami‐Dade County in Florida, Baltimore city in Maryland, and Bronx County in New YorkConclusionThe state‐ and county‐specific estimates could help public health officials to understand the burden of disease (e.g., demand for caregiver counseling and institutional care) and develop strategies for identifying and caring for people with Alzheimer’s dementia

A Comprehensive 16-Year Analysis of National Center for Health Statistics Data on the Top Three Causes of Death Before Age 75 by Sex, Race, and Hispanic Origin.

This study aimed to conduct a comprehensive 16-year analysis of years of potential life lost (YPLL) due to leading causes of death in the United States, focusing on disparities by sex, race/ethnicity, and specific causes of death using the National Center for Health Statistics (NCHS) data. Data from the NCHS spanning 2000-2016 were included. Age-adjusted YPLL rates per 100,000 population were analyzed, stratified by sex, race/ethnicity, and leading causes of death, including malignant neoplasms, heart disease, and cerebrovascular diseases. Over 16 years, the total YPLL rate was 7,036.2 per 100,000 population. Males had a higher YPLL rate (8,852.5 per 100,000) than females (5,259.9 per 100,000). Among racial/ethnic groups, Black/African Americans had the highest YPLL rate (10,896.8 per 100,000), followed by American Indian/Alaska Natives (7,310.0 per 100,000), Hispanics/Latinos (5,256.8 per 100,000), and Asians/Pacific Islanders (3,279.7 per 100,000). Leading causes included malignant neoplasms (1,451.6 per 100,000), heart diseases (1,055.4 per 100,000), and cerebrovascular diseases (182.3 per 100,000). This analysis spanning 16 years highlights notable disparities in YPLLrates among different demographic groups. These differences are evident in the YPLL rates for males, which are higher than those for females. The YPLL rate is most pronounced among Black/African Americans, followed by American Indian/Alaska Natives, Hispanics/Latinos, and Asians/Pacific Islanders. The primary contributors to YPLL are malignant neoplasms, heart diseases, and cerebrovascular diseases. These findings emphasize the importance of addressing these disparities to enhance public health outcomes and mitigate the premature loss of life.Despite progress, disparities persist, highlighting the need for targeted interventions and further research.

Epidemiology of Current Asthma in Children Under 18: A Two-Decade Overview Using National Center for Health Statistics (NCHS) Data.

This study conducted a comprehensive two-decade analysis of current asthma among children under 18 in the United States using National Center for Health Statistics (NCHS) data. The primary objective was to assess the prevalence of current asthma, evaluate temporal trends, and identify disparities based on gender, age, insurance status, household poverty levels, and race/ethnicity. Data spanning 2003-2019 from NCHS were analyzed, focusing on current asthma prevalence among children under 18. Age-adjusted prevalence rates were calculated and stratified by various factors, including gender, age groups, health insurance status, poverty levels, and race/ethnicity. The study revealed substantial disparities in current asthma prevalence. Over the two-decade period, the overall prevalence of current asthma fluctuated. It increased from 2003 (8.5%) to 2009 (9.6%) and then decreased by 2019 (7.0%). Gender disparities were evident, with males (9.9%) consistently reporting a higher prevalence than females (7.5%). Older children aged between 10-17 years (10.4%) consistently had a higher prevalence of asthma than younger children aged 0-4 (5.3%) and 5-9 years (9.5%). Children with Medicaid insurance (11.2%) had the highest prevalence, followed by insured (8.9%), privately insured (7.7%), and uninsured children (6.1%). Children living below the federal poverty level (FPL) consistently reported the highest prevalence (11.3%), while children above 400% of the FPL (7.1%) had the lowest prevalence. Racial disparities were observed, with Black children (14.3%) having higher asthma prevalence, followed by White (7.6%) and Asian children (5.4%). The study highlights significant disparities in current asthma prevalence over the two-decade period analyzed. While the overall prevalence showed fluctuations, it generally increased from 2003 to 2009 and then decreased by 2019. Gender disparities were evident, with males consistently reporting a higher prevalence compared to females. Older children in the 10-17 age group consistently had a higher asthma prevalence than younger age groups. Moreover, disparities based on insurance status and income levels were also apparent, with children on Medicaid and those living below the FPL reporting higher asthma prevalence. Racial disparities were observed, with Black children having the highest prevalence, followed by White and Asian children. These findings emphasize the importance of addressing these disparities and tailoring interventions to improve asthma management and prevention across different demographic groups.

Attention-Deficit Hyperactivity Disorder Among American Youth: A Comprehensive 20-Year Analysis of National Center for Health Statistics (NCHS) Data

Attention-Deficit Hyperactivity Disorder Among American Youth: A Comprehensive 20-Year Analysis of National Center for Health Statistics (NCHS) Data

Prognostic value of NT-proBNP and cardiac troponin levels in ambulatory patients with congestive heart failure - Insight from NHANES

Abstract Background Recently there has been increased interest in the utility of cardiac troponin and NT-proBNP to predict the prognosis in patients with CHF. The aim of this study was to investigate the prognostic significance of NT-proBNP and cardiac troponin in CHF patients in ambulatory settings. Methods The NHANES, conducted by the National Center for Health Statistics, collects nationally representative data on the health and nutritional status of the non-institutionalized US population. We included heart failure patients aged ≥ 40 years with valid entries for NT-proBNP and cardiac troponin. We used data collected during the period 1999 -2004. The primary endpoint was all-cause mortality. Vital status (dead or alive) was determined by linkage to a record match of the National Death Index, conducted by the National Center for Health Statistics through December 31, 2020. Follow up period was from the examination date to either the date of death or December 31, 2020, whichever came first. NT-proBNP and cardiac troponin levels were stratified into tertiles, and mortality was assessed using cox proportional hazard mortality multivariate logistic regression models. K-M survival curves were used to display mortality over time. All analyses were done using STATA version 17, with p-values less than 0.05 considered statistically significant. Results In all, there were 551 persons, corresponding to 4.4 million, with a diagnosis of CHF. Of this, 379, corresponding to 4.1 million persons, were retained for analyses. Hypertension (61.6%), diabetes (34.26%), CKD (32.7%), nicotine use (65.45%), and cardiovascular diseases (CVD) were the most prevalent comorbidities. On the multivariate analysis, compared to lower tertile for elevated NT-proBNP, being in the middle tertile increased the risk of all-cause mortality up to 54% (HR 1.54, CI 1.03 – 2.3, P = 0.035) and up to 2 fold for being in upper tertile (HR 1.95, CI 1.29 – 2.96, P = 0.002)(Figure 1). Similarly, compared to the lower tertile for elevated troponin, being in the upper tertile increased the risk of all-cause mortality up to threefold (HR 2.84, CI 1.82- 4.44, P = 0.000) while being in the middle tertile could not achieve statistical significance for predicting the outcome (HR 1.44, CI 0.95 - 2.17, P = 0.082)(Figure 2). Among other predictors included in the analysis, CKD and history of smoking were associated with overall worse survival (HR 1.68, CI 1.25- 2.23, P = 0.000) and (HR 1.5, CI 1.099-2.076, P = 0.011), respectively. Conclusion CHF patients in the middle and upper tertile for NT-proBNP and cardiac troponin compared to the lower tertile showed an overall poor prognosis on follow up in the ambulatory settings. Our findings suggest that monitoring NT-proBNP and cardiac troponin levels can be useful tools for predicting prognosis. Further studies are needed for the clinical implications of this strategy.K-M survival estimates for NT-proBNPK-M survival estimates for troponin