Wide-ranging Online Data For Epidemiologic Research Research Articles

Trends and disparities in cardiac implantable electronic device infection-related mortality in the United States.

We performed a cross-sectional study using the Centers for Disease Control and Prevention's (CDC's) Wide-Ranging Online Data for Epidemiologic Research (WONDER) database to analyze the trends in cardiac implantable electronic device (CIED) infection-related mortality from 1999 to 2020. We analyzed the death certificate data from the CDC WONDER database from 1999 to 2020 for CIED infections in the US population aged ≥25 years usingInternational Classification of Diseases, Tenth Revision(ICD-10) codes, listed as the underlying or contributing cause of death. Age-adjusted mortality rates (AAMR) and 95% confidence intervals (CIs) were computed per 1 million population by standardizing crude mortality rates to the 2000 US census population. To assess annual mortality trends, we employed the Joinpoint regression model, calculating the annual percent change (APC) in AAMR and corresponding 95% CIs. Overall, there was an observed declining trend in AAMRs related to CIED infection-related mortality. Males accounted for 55% of the total deaths, with persistently higher AAMRs compared to females over the study duration. Both males and females had an overall decreasing trend in AAMRs throughout the study duration. On race/ethnicity stratified analysis, non-Hispanic (NH) Blacks exhibited the highest overall AAMR, followed by NH American Indians or Alaska Natives, NH Whites, Hispanic or Latinos, and NH Asian or Pacific Islanders. On a stratified analysis based on region, the South region had the highest overall AAMR, followed by the Midwest, West, and Northeast regions. Our study demonstrates a significant decline in CIED infection-related mortality in patients over the last two decades. Notable gender, racial/ethnic, and regional differences exist in the rates of mortality related to CIED infections.

A Longitudinal Analysis of Mortality Related to Chronic Viral Hepatitis and Hepatocellular Carcinoma in the United States

(1) Background: Hepatocellular carcinoma (HCC) contributes to the significant burden of cancer mortality in the United States (US). Despite highly efficacious antivirals, chronic viral hepatitis (CVH) remains an important cause of HCC. With advancements in therapeutic modalities, along with the aging of the population, we aimed to assess the contribution of CVH in HCC-related mortality in the US between 1999–2020. (2) Methods: We queried all deaths related to CVH and HCC in the multiple-causes-of-death files from the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) database between 1999–2020. Using the direct method of standardization, we adjusted all mortality information for age and compared the age-adjusted mortality rates (AAMRs) across demographic populations and by percentile rankings of social vulnerability. Temporal shifts in mortality were quantified using log-linear regression models. (3) Results: A total of 35,030 deaths were identified between 1999–2020. The overall crude mortality increased from 0.27 in 1999 to 8.32 in 2016, followed by a slight reduction to 7.04 in 2020. The cumulative AAMR during the study period was 4.43 (95% CI, 4.39–4.48). Males (AAMR 7.70) had higher mortality rates compared to females (AAMR 1.44). Mortality was higher among Hispanic populations (AAMR 6.72) compared to non-Hispanic populations (AAMR 4.18). Higher mortality was observed in US counties categorized as the most socially vulnerable (AAMR 5.20) compared to counties that are the least socially vulnerable (AAMR 2.53), with social vulnerability accounting for 2.67 excess deaths per 1,000,000 person-years. (4) Conclusions: Our epidemiological analysis revealed an overall increase in CVH-related HCC mortality between 1999–2008, followed by a stagnation period until 2020. CVH-related HCC mortality disproportionately affected males, Hispanic populations, and Black/African American populations, Western US regions, and socially vulnerable counties. These insights can help aid in the development of strategies to target vulnerable patients, focus on preventive efforts, and allocate resources to decrease HCC-related mortality.

Availability of Primary Care Physicians and Racial Disparities in Colorectal Cancer-Related Mortality in the United States.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States (US), however racial disparities in outcomes persist. We sought to assess the correlation of availability of primary care physicians (PCPs) and racial disparities in CRC-related mortality. We studied the correlation between age-adjusted incidence and mortality rates of CRC among all 50 states and the District of Columbia (D.C.) from the Center for Disease Control (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) with the number of actively practicing PCPs in all 50 states and D.C. from the Association of American Medical Colleges (AAMC) State Physician Workforce Data Report. Pearson's coefficient was used to study correlations and the two-sample t test was used for comparing state-level PCP/CRC ratios between the two groups. Statistical analysis was performed using VassarStats. The mean AAMR per 100,000 population for CRC was significantly higher among AA versus White populations (t = 5.79, p < 0.001). Higher state-wide PCP per CRC case ratio correlated with lower state-wide CRCrelated mortality (r = -0.36, p = 0.011). The mean PCP per CRC case ratio was significantly lower among AA compared to White populations (t = -15.95, p < 0.0001). Higher PCP per CRC case ratio correlated with lower CRC-related mortality among both White (r = -0.64, p < 0.0001) and AA (r = -0.57, p = 0.0002) populations. These findings suggest that racial disparities in CRC-related mortality may at least in part be related to lower availability of PCPs. Efforts focused on the development of strategies focused on improving access to primary care may help bridge racial disparities in CRC-related outcomes.

Saving Hearts in Rural West Texas: The Impact of Critical Care Access on Mortality Rates.

Background The Critical Access Hospital (CAH) designation program was created in 1997 by the US Congress to reduce the financial vulnerability of rural hospitals and improve access to healthcare by keeping fundamental services in rural communities. Methods This is a retrospective observational study. Information on CAHs in West Texas in rural counties was extrapolated from the Flex Monitoring Team between 2010 and 2020. The study population included adults aged ≥25 years with a known heart failure (HF) diagnosis who were identified using ICD-10 codes. Mortality rates were obtained from the CDC Wide-ranging ONline Data for Epidemiologic Research (WONDER) database. The HF population was categorized by age, sex, and ethnicity. Mortality differences among these groups were analyzed using a two-sample t-test. The significance level was considered to be p < 0.05. Results The total study population analyzed was 1,348,001. A statistically significant difference in age-adjusted mortality rate (AAMR) was observed between the study and control groups, with a value of 3.200 (95% CI: 3.1910-3.2090, p < 0.0001) in favor of a lower mortality rate in rural counties with CAHs. When comparing gender-related differences, males and females had lower AAMRs in rural counties with CAHs. Among each gender, statistically significant differences were noted between males (95% CI: 2.181-2.218, p < 0.001) and females (95% CI: 3.382-3.417, p < 0.001). When examining the data by ethnicity, the most significant difference in mortality rate was observed within the Hispanic population, 6.400 (95% CI: 6.3770-6.4230, p < 0.0001). When adjusted to age, the crude mortality rate was calculated, which favored CAH admission in the younger population (10.200 (95% CI: 10.1625-10.2375, p < 0.001) and 11.500 (95% CI: 11.4168-11.5832, p < 0.001) in the 55-64 and 65-74 age groups, respectively). Conclusion The data clearly showed that West Texas rural county hospitals that received CAH designation performed better in terms of mortality rates in the HF population compared to non-CAH.

Trends of hypertrophic cardiomyopathy-related mortality in United States young adults: a nationwide 20-year analysis.

Data regarding hypertrophic cardiomyopathy (HCM)-related mortality in United States young adults, defined as those aged between 25 and 44 years, are lacking. We sought to assess the trends in HCM-related mortality among US young adults between 1999 and 2019 and determine differences by sex, race, ethnicity, urbanization and census region. Mortality data were retrieved by the Centers for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiologic Research (WONDER) dataset from January 1999 to December 2019. Age-adjusted mortality rates (AAMRs) were assessed using the Joinpoint regression modeling and expressed as estimated average annual percentage change (AAPC) with relative 95% confidence intervals (95% CIs). Over 20-year period, the AAMR from HCM in US young adults linearly decreased, with no differences between sexes [AAPC: -5.3% (95% CI -6.1 to -4.6), P < 0.001]. The AAMR decrease was more pronounced in Black patients [AAPC: -6.4% (95% CI -7.6 to -5.1), P < 0.001], Latinx/Hispanic patients [AAPC: -4.8% (95% CI -7.2 to -2.36), P < 0.001] and residents of urban areas [AAPC: -5.4% (95% CI -6.2 to -4.6), P < 0.001]. The higher percentages of HCM-related deaths occurred in the South of the country and at the patient's home. HCM-related mortality in US young adults has decreased over the last two decades in the United States. Subgroup analyses by race, ethnicity, urbanization and census region showed ethnoracial and regional disparities that will require further investigation.

The impact of civil commitment laws for substance use disorder on opioid overdose deaths.

Our study analyzed the impact of civil commitment (CC) laws for substance use disorder (SUD) on opioid overdose death rates (OODR) in the U.S. from 2010-21. We used a retrospective study design using the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) dataset to analyze overdose death rates from any opioid during 2010-21 using ICD-10 codes. We used t-tests and two-way ANOVA to compare the OODR between the U.S. states with the law as compared to those without by using GraphPad Prism 10.0. We found no significant difference in the annual mean age-adjusted OODR from 2010-21 between U.S. states with and without CC SUD laws. During the pre-COVID era (2010-19), the presence or absence of CC SUD law had no difference in age-adjusted OODR. However, in the post-COVID era (2020-21), there was a significant increase in OODR in states with a CC SUD law compared to states without the law (p = 0.032). We also found that OODR increased at a faster rate post-COVID among both the states with CC SUD laws (p < 0.001) and the states without the law (p = 0.019). We found higher age-adjusted OODR in states with a CC SUD law which could be due to the laws being enacted in response to the opioid crisis or physicians' opposition to or unawareness of the law's existence leading to underutilization. Recent enactment of CC SUD law(s), a lack of a central database for recording relapse rates, and disparities in opioid overdose rate reductions uncovers multiple variables potentially influencing OODR. Thus, further investigation is needed to analyze the factors influencing OODRs and long-term effects of the CC SUD laws.

Abstract WMP103: Tightening of the Stroke Belt

Background: Higher stroke mortality in the Southeastern United States has been recognized for over 80 years, but recent trends from in Stroke Belt (SB) vs non-SB stroke death rates have not been well delineated. Methods: We analyzed stroke-related annual age-adjusted mortality rates (AAMR) in the CDC Wide-Ranging Online Data for Epidemiologic Research (WONDER) database from 1999-2019, comparing the 8 SB states (Alabama, Arkansas, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, and Tennessee) and 42 non-SB states among all individuals and subgroups of age, sex, race-ethnicity, and urban-rural. AAMRs reported per 100,000 individuals. Results: Throughout the 1999-2019 period, AAMRs were higher in the SB than non-SB. Both SB and non-SB states showed rapid AAMR decline from 1999 - 2009, then slow decline 2009-2014, and plateau 2014-2019. Yet, SB AAMR declined more rapidly. AAMRs in 1999, 2009, and 2019 in the SB were 122.60, 80.54, and 73.52; in the non-Stroke Belt 100.84, 64.14, and 61.35). As a result, the number of SB states with substantially elevated AAMR compared with non-SB states fell from 7 in 1999 to 6 in 2009 and 2 (MS, TN) in 2019 (Figure). Age, sex, and urban-rural subgroup trends resembled the overall population. Yet, race-ethnic variations were noted. Throughout the study period in the SB, Black individuals had the highest AAMRs but had a steeper decline than White individuals, with the gap narrowing from 49.50 (163.06 vs 113.56) in 1999 to 28.45 (96.97 vs 68.52) in 2019. AAMRs for Hispanic and Asian individuals were lower than White individuals throughout the study period in the SB and dropped more steeply for Asian (76.18 to 46.76) than Hispanic individuals (54.50 to 35.61). Conclusions: Stroke mortality declined more steeply between 1999-2019 in the Southeastern US than the rest of the country. Substantial SB race-ethnic disparities persist, with AAMRs highest in Black, intermediate in White, and lowest in Asian and Hispanic individuals.

Association Between the New York SAFE Act and Firearm Suicide and Homicide: An Analysis of Synthetic Controls, New York State, 1999‒2019.

Objectives. To assess the association between the New York Secure Ammunition and Firearms Enforcement Act (NY SAFE Act) and firearm suicide and homicide rates. Methods. We employed a synthetic controls approach to investigate the impact of the NY SAFE Act on firearm suicide and firearm homicide rates. We collected state-level data on firearm mortality from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research (WONDER) database for the period 1999-2019. We derived statistical inference by using a permutation-based in-place placebo test. Results. The implementation of the NY SAFE Act was associated with a significant reduction in firearm homicide rates, demonstrating a decrease of 63%. This decrease corresponds to an estimated prevention of 1697 deaths between 2013 and 2019. However, there was no association between the NY SAFE Act and firearm suicide rates. Conclusions. As the responsibility for enacting firearm policies increasingly falls on states instead of the federal government, this study provides valuable information that can assist states in making evidence-based decisions regarding the development and implementation of firearm policies that prioritize public safety and aim to prevent firearm-related fatalities. (Am J Public Health. 2023;113(12):1309-1317. https://doi.org/10.2105/AJPH.2023.307400).

Quantitative Opiate, Opioid, and Benzodiazepine Testing by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS).

Fatalities due to opioids and other controlled substances continue to increase year over year and maintain an epidemic level nationally. CDC data indicates that drug overdoses killed more than 100,000 Americans in 2021 with synthetic opioids being the main driver of the national crisis (Wide-ranging online data for epidemiologic research (WONDER). Multiple Cause of Death 1999-2020. Centers for Disease Control and Prevention, National Center on Health Statistics. http://wonder.cdc.gov . Accessed 28 Feb 2023, 2021). Response to this crisis includes the development of laboratory testing to support the evolving drug trends. Urine drug testing provides clinicians with objective information to assist in making treatment decisions by identifying the presence of potential drugs of abuse and assessing patient compliance to a controlled substance prescription regimen. In this chapter, we describe a rapid LC-MS/MS method for the simultaneous quantitation of 21 opiate, opioid, and benzodiazepine drugs in less than 4min. The method requires 100uL of urine and includes enzymatic hydrolysis of glucuronide conjugates using β-glucuronidase to provide total drug measurement. Quantitation is accomplished using multiple reaction monitoring (MRM), a seven-point calibration curve, and deuterated internal standards. This method provides a robust and reliable means to measure commonly prescribed opioid (including natural, semi-synthetic, and synthetic) and benzodiazepine drugs in urine.

Assessment of racial/ethnic representation in Alzheimer’s disease genetics datasets

AbstractBackgroundBiased representation of populations in genetic research leads to disparities in genetics knowledge and utility. Here, we compare the racial/ethnic demographics of all participants in nationally funded Alzheimer’s disease (AD) genetics cohorts to demographics of US AD mortality.MethodsWe used death certificate data from the CDC Wide‐ranging Online Data for Epidemiologic Research (WONDER) Database to calculate age‐adjusted AD mortality of adults aged 65 years and older for 2016‐2020. We compared the racial/ethnic distributions in mortality to the racial/ethnic distribution of AD genetics participants across 16 studies in the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) that met the following filters: Disease = `AD`; Molecular Data = `Genotype`; and Type = `GWAS` as well as five studies in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. Demographic data was obtained directly from data or via literature review. In addition to the GWAS data, we also compared racial demographic data from sequencing studies released as part of the Alzheimer’s Disease Sequencing Project (ADSP) Umbrella (dssNIAGADS NG00067).ResultsTable 1 describes the racial/ethnic distribution of the age‐adjusted AD mortality rate of the US population from 2016‐2020. Non‐Hispanic Whites had the highest rate (per 100,000 person‐years): 254.2 (95% CI 253.5‐254.9), and Asian or Pacific Islander (AS/PI) had the lowest rate: 125.6 (123.6‐127.71). The racial/ethnic distribution of the 13,909 AD cases across 21 genotype datasets available in NIAGADS or CHARGE are presented in Table 1. Most (87.6%) of AD cases are non‐Hispanic White, with the least (0.25%) being AS/PI. Preliminary analysis of ADSP data show increased proportions of Hispanic and Black participants (Table 1).ConclusionThe racial/ethnic distribution of AD genetics participants is representative of proportion of deaths, but after adjusting for age and population distribution, AS/PI have 50% lower mortality rate compared to non‐Hispanic Whites while comprising less than 5% of participants in genetics cohorts. While progress is being made to diversify sequencing data, AS/PI and American Indian or Alaska Natives remain underrepresented in AD genetics research, which may lead to inequitable benefits from future research and pharmaceutical treatments.

Epidemiological Trends and Factors Associated With Mortality Rate in Psychoactive Substance Use-Related Mental and Behavioral Disorders: A CDC-WONDER Database Analysis.

Background The persisting challenge of substance use disorder's impact on society prompts the need for insights into its mortality trends. This study examines epidemiological patterns and factors tied to mortality rates in individuals with psychoactive substance-related mental and behavioral disorders from 1999 to 2020. Methodology This study used a retrospective observational design. The study analyzed the Centers for Disease Control and Prevention's (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database information, encompassing mortality and population-based data. Data extraction focused on specific criteria such as age, sex, race/ethnicity, and geographic location. Descriptive statistics were employed to depict the study population and reveal epidemiological trends. Results The study encompassed data from 239,573 individuals who died due to psychoactive substance use-related mental and behavioral disorders between 1999 and 2020. The overall mortality rate was 3.55 per 100,000 individuals (95% confidence interval (CI) = 3.55-3.54) across the study period. Noticeable discrepancies in mortality rates emerged among various geographic regions, genders, races, and age groups. Males (5.32 per 100,000 individuals) experienced notably higher mortality rates than females (1.80 per 100,000 individuals), while the 55-64 age group faced elevated mortality risks (8.24 per 100,000 individuals) compared to the 25-34 age group (1.71 per 100,000 individuals). Significant variations in mortality rates were also evident across different racial and ethnic groups. Conclusions Between 1999 and 2020, the study explored mortality rates in individuals with psychoactive substance use-related mental and behavioral disorders. This analysis revealed variations in mortality across genders, ages (with the 55-64 age group facing higher risks compared to the 25-34 age group), and ethnicities. Notably, males exhibited higher mortality than females. Additionally, divergent rates were observed among different geographic regions. These insights can inform public health initiatives and support the development of targeted strategies to reduce mortality rates and improve the well-being of affected individuals.

The Impact of Non-Adherence to Antihypertensive Drug Therapy.

Medication non-adherence is a major healthcare barrier, especially among diseases that are largely asymptomatic, such as hypertension. The impact of poor medication adherence ranges from patient-specific adverse health outcomes to broader strains on health care system resources. The Centers for Disease Control (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database was used to retrieve Centers for Medicare and Medicaid Services' data pertaining to blood pressure (BP) medication adherence, socio-economic variables, and cardiovascular (CV) outcomes across the United States. Multivariable linear regression models were used to estimate the change in total CV deaths as a function of non-adherence to BP medications. For every percent increase in the non-adherence rate, the total number of CV deaths increased by 7.13 deaths per 100,000 adults (95% CI: 6.34-7.92), even after controlling for the percentage of residents with access to insurance, the percentage of residents who were eligible for Medicaid, the percentage of residents without a college education, median home value, income inequality, and the poverty rate (p < 0.001). There is a significant association between non-adherence to BP medications and total CV deaths. Even a one percent increase in the adherence rate in the United States could result in tens of thousands of preventable CV deaths. Based on recently published CDC data, this could also have a tremendous impact on health care costs. This provides compelling evidence for increased efforts to improve adherence.

Trends in Location of Death for Individuals With Ovarian Cancer in the United States.

Using the publicly available Centers for Disease Control and Prevention's WONDER (Wide-ranging Online Data for Epidemiologic Research) database from 2003 to 2019, we evaluated associations between decedent characteristics and location of death for patients with ovarian malignancy. We found that Black, Native American, Asian American, and Hispanic patients were more likely to die in hospitals than White patients, despite an overall reduction in hospital deaths and an overall increase in hospice facility deaths. Additionally, patients with lesser educational attainment were more likely to die in nursing facilities and less likely to die in hospice facilities. Although there may be some contribution from cultural preferences, these findings may represent disparities in access to palliative care affecting people with cancer from racial and ethnic minoritized groups.

Abstract 18319: Regional Disparities in the Cardiovascular Deaths Among Sarcoidosis Patients: A CDC-Wonder Database Analysis From 2005-2020

Background: Sarcoidosis can manifest as “Cardiovascular Death (CVD)” in undiagnosed patients. Regional Impact and Disparities In CVDs among sarcoidosis have not been identified. Methods: We analyzed data from the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database from January 2005, to December 2020. All deaths related to CVS were included from 4 different regions. Data for deaths related to sarcoidosis and CVD were obtained by querying “Sarcoidosis” using ICD 10th Revision code “D86”. Rates per year for trends and disparities were calculated using cumulative CVD. Results: A total of 8211 CVD from 2005-2020 were identified among sarcoid patients- 1666, (20.2%) in north east, 1,697 (20.64%) in midwest, 3,684 (44.81%) in south and 1,164, (14.15%) in west . The CVDs occurred mostly in the ages(55-74) in the northeast, (45-74) in the Midwest, (35-84) in the south and (45-84) in the west. Incidence of cardiovascular death among females with sarcoid was greater than males in all regions .(12.03% vs 8.25% in northeast , 12.65% vs 8.02% in midwest , 8.12 %vs 6.05% in west , 27.13%v/s 17.73% in south ). The South showed a significantly higher population of blacks suffering from CVD (31.3% blacks vs 12.61% whites) whereas in other regions , the rates were comparable. The most common cause of CV death was found to be cardiac arrest (28.8 %) in the north east, cardiomyopathy(27.09%) in the midwest , cardiac arrhythmias (17.13%) in the west and conduction disorders (52.17%) in the south. An increasing trend of CVD was recorded in the south with an increase in rates from 42.5% in 2005 to 45% in 2020. Conclusion: Incidence of CVD related to sarcoidosis is highest in the south and females had higher mortality in all regions. Pulmonary hypertension, cardiac arrest and CHF were the major causes of CVD.

Geographically Weighted Modeling to Explore Social and Environmental Factors Affecting County-Level Cardiovascular Mortality in People With Diabetes in the United States: A Cross-Sectional Analysis

Disparities exist in the cardiovascular mortality rates among people with type 2 diabetes (T2D). Research has established that these disparities are often related to the environmental and social determinations of health. This study explores the spatial variation between air pollution, social determinants of health and T2D related age-adjusted cardiovascular mortality (aa-CVM) in the United States. We obtained county-level T2D related to aa-CVM (per 100,000 residents) from Centers for Disease Control and Prevention WONDER (Wide-ranging Online Data for Epidemiologic Research) (2010 to 2019). We fit a geographically weighted linear regression with aa-CVM as the outcome and the following covariates (ambient air pollution [particulate matter of 2.5 µm size], median annual household income, racial/ethnic minorities, higher education, rurality, food insecurity, and primary health care access) were included. Overall, the median aa-CVM rate was 92.9 and highest in the South (102.2). In the West, aa-CVM was significantly associated with particulate matter of 2.5 µm size, annual median household income, racial minority status and primary health care access. Food insecurity was the most significant exposure in the Midwest and Northeast, while in the South, annual median household income and food insecurity were significant. In conclusion, this study demonstrated a substantial regional variation of exposure to determinants of T2D related aa-CVM in the United States. These findings should be considered in policy frameworks and interventions as part of community-level approaches to addressing T2D related aa-CVM, and within broader state and national discussions of the importance of population health.

Trends and Factors Associated With Mortality Rates of Leading Causes of Infant Death: A CDC Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Database Analysis.

Infant mortality is a critical indicator of a nation's healthcare system and social well-being. This study explores trends and factors associated with mortality rates for three leading causes of infant death: congenital malformations, deformations, and chromosomal abnormalities; disorders related to short gestation and low birth weight, not elsewhere classified; and sudden infant death syndrome (SIDS). Utilizing the CDC WONDER (CDC Wide-Ranging Online Data for Epidemiologic Research) database, we conducted a retrospective observational analysis of infant mortality rates and associated factors. Data encompassed multiple years, allowing for trend analysis and exploration of influencing variables. Study variables included demographic, maternal, prenatal, and leading cause as factors. Trends in infant mortality rates varied across causes. The overall mortality rate was 2.69 per 1,000 (p=0.000) people during 2007-2020. The highest rates were observed in 2007 (3.05), 2008 (3.01), and 2009 (2.93) per 1,000 infants. For congenital malformations, deformations, and chromosomal abnormalities, the rate ranged from 1.35 to 1.12 (2007-2020). Gender-based mortality differences were subtle (male rate 2.88 per 1,000 infants, p=0.000; female infants 2.50 per 1,000 infants, p=0.000). The examination of infant mortality trends also explored maternal variables, including maternal age, education, and delivery method. The analysis revealed disparities across variables. Teenage maternal age correlated with higher mortality rates, while maternal education was associated with lower rates. Vaginal delivery (2.61 per 1,000 infants, p=0.199) showed slightly lower rates compared to cesarean section (2.86 per 1,000 infants, p=0.076). This study utilizes the CDC WONDER database and offers evidence of changing trends in infant mortality rates for the selected causes. Factors such as maternal age (30-34 years and 35-39 years), race/ethnicity (Black or African-American and White), birthplace (in hospital), and mother's education (master's degree) were identified as influencing mortality rates. These findings contribute to informed policymaking and interventions aimed at mitigating infant mortality and improving the well-being of infants and their families. Further research is needed to fully understand the underlying dynamics of these trends and factors.

Epidemiological Trends and Factors Associated With the Morbidity Rate of Gonorrhea: A CDC-WONDER Database Analysis.

Gonorrhea is a prevalent sexually transmitted illness caused by the bacteria Neisseria gonorrhoeae, leading to serious health consequences such as pelvic inflammatory disease (PID), infertility, ectopic pregnancy, and increased susceptibility to HIV infection. Despite advancements in prevention and treatment, gonorrhea remains a significant public health problem in the United States (US) due to its widespread incidence, potential consequences, and the growth of antibiotic resistance. This study investigates the epidemiological trends and morbidity rates of gonorrhea using theCenters for Disease Control and Prevention's (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database. The aim is to identify temporal patterns, demographic characteristics, and notable changes in gonorrhea epidemiology to inform targeted therapies and interventions. The CDC WONDER database, which provides extensive national and state-level data on reported causes of death in the United States, was utilized for this study. We examined the developments in gonorrhea morbidity rates over time, identified demographic differences based on age, gender, and race/ethnicity, and analyzed the disease's regional distribution through a systematic analysis of the database. Aggregate data for selected time periods (1996-2014) were summarized using the morbidity rate per 100,000 people and the total number of cases across the years. This database analysis identified a total of 6,454,097 individuals diagnosed with gonorrhea between 1996 and 2014. The calculated total morbidity rate during this period was 115.4 per 100,000 individuals. The highest morbidity rates were observed in the years 1999 (129.2 per 100,000 people), 1998 (129.1 per 100,000 people), and 2001 (126.8 per 100,000 people), respectively. The District of Columbia reported the highest morbidity rate (478.25 per 100,000 people). In males, the overall morbidity rate over the years was reported to be comparable to females (114 per 100,000 people and 116.3 per 100,000 people, respectively). The analysis revealed consistently higher morbidity rates among individuals aged between 19 and 24 years (525.2 per 100,000 people). Moreover, black or African American individuals consistently exhibited higher morbidity rates (506.1 per 100,000 people) compared to white individuals (16.1 per 100,000 people). The analysis of gonorrhea cases between 1996 and 2014 revealed that the highest rates occurred during specific years, with a particular concentration observed in the District of Columbia. Additionally, certain demographic groups, such as individuals aged 19-24 and the black or African American population, consistently exhibited higher morbidity rates compared to others. These findings emphasize the importance of targeted interventions to address the observed temporal patterns and demographic disparities, in order to effectively combat the spread of gonorrhea.

Suicide Risk Among Patients With Heart Disease and Heart Failure

Heart disease is the leading cause of death in the United States (US). Suicide is the 12th leading cause of death. However, little is known about the risk of suicide in patients with heart disease and heart failure. Using Multiple Cause of Death data from the Centers for Disease Control and Prevention (CDC) Wide-ranging ONline Data for Epidemiologic Research (WONDER) database, we used a cross-sectional analysis to examine the risk of suicide in patients with heart disease and heart failure as compared with the general US population and in subgroups within the US. We assessed suicide rate in patients with heart disease and heart failure in the US population as a whole and stratified by race, time, urbanization levels, and census regions using the CDC WONDER Multiple Cause of Death database. Standardized mortality rates were calculated as observed deaths divided by expected deaths. As compared with the general population, patients with heart disease and heart failure had an elevated risk of suicide. This was true across racial and geographic subgroups. There was an elevated risk of suicide in patients with heart disease and heart failure in the United States. For heart disease, there were particular elevations in the Western US, and there was a particular elevation in Black Americans compared with the age-matched population.

Temporal trends and geographic variations in mortality rates from tobacco and firearms in the United States

We explored temporal trends and geographic variations in United States of America (US) mortality rates from smoking and firearms from 1999 to 2019. To do so, we used the publicly available Centers for Disease Control and Prevention (CDC) Wide Ranging Online Data for Epidemiologic Research (WONDER) with Multiple Cause of Death files from 1999 to 2019. Using age-specific rates and ArcGIS Pro Advanced software for Optimized Hot Spot Analyses from Esri, we generated maps of statistically significant spatial clusters with 90–99% confidence intervals with the Getis-Ord Gi* statistic for mortality from smoking-related causes and firearms.These data show temporal trends and geographic variations in mortality from smoking and firearms in the US. Smoking and firearm-related mortality from assault and suicide increased throughout the US and clustered in the Southeast. Firearm-related suicide also clustered in the continental West and Alaska. These descriptive data generate many hypotheses which are testable in analytic epidemiologic studies designed a priori to do so. The trends suggest smoking and firearm-related causes pose particular challenges to the Southeast and firearms also to the West and Alaska. These data may aid clinicians and public health authorities to implement evidence-based smoking avoidance and cessation programs as well as address firearm mortality, with particular attention to the areas of highest risks. As has been the case with cigarettes, individual behavior changes as well as societal changes are likely to be needed to achieve decreases in premature mortality.

County-Level Income Inequality, Social Mobility, and Deaths of Despair in the US, 2000-2019

Increasing mortality from suicide, drug overdose, and alcohol-related liver disease (collectively referred to as deaths of despair) is a critical public health crisis. Income inequality and social mobility have been separately associated with all-cause mortality; however, no studies have examined their interaction with these preventable deaths. To assess the interaction between income inequality and social mobility with deaths of despair among working-age Hispanic, non-Hispanic Black, and non-Hispanic White populations. This cross-sectional study analyzed data from the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database on county-level deaths of despair from 2000 to 2019 across racial and ethnic groups. Statistical analysis was performed from January 8 to May 20, 2023. The primary exposure of interest was county-level income inequality, measured by the Gini coefficient. Another exposure was race- and ethnicity-specific absolute social mobility. Tertiles for the Gini coefficient and social mobility were created to evaluate the dose-response association. The main outcomes were adjusted risk ratios (RRs) of deaths from suicide, drug overdose, and alcoholic liver disease. The interaction between income inequality and social mobility was formally tested on both the additive and multiplicative scales. The sample included 788 counties for Hispanic populations, 1050 counties for non-Hispanic Black populations, and 2942 counties for non-Hispanic White populations. Over the study period, 152 350, 149 589, and 1 250 156 deaths of despair were recorded for working-age Hispanic, non-Hispanic Black, and non-Hispanic White populations, respectively. Compared with the reference group (counties with low income inequality and high social mobility), counties with greater income inequality (high inequality: RR, 1.26 [95% CI, 1.24-1.29] for Hispanic populations; RR, 1.18 [95% CI, 1.15-1.20] for non-Hispanic Black populations; and RR, 1.22 [95% CI, 1.21-1.23] for non-Hispanic White populations) or less social mobility (low mobility: RR, 1.79 [95% CI, 1.76-1.82] for Hispanic populations; RR, 1.64 [95% CI, 1.61-1.67] for non-Hispanic Black populations; and RR, 1.38 [95% CI, 1.38-1.39] for non-Hispanic White populations) had higher RRs for deaths of despair. In counties with high income inequality and low social mobility, positive interactions were observed on the additive scale for Hispanic populations (relative excess risk due to interaction [RERI], 0.27 [95% CI, 0.17-0.37]), non-Hispanic Black populations (RERI, 0.36 [95% CI, 0.30-0.42]), and non-Hispanic White populations (RERI, 0.10 [95% CI, 0.09-0.12]). In contrast, positive interactions on the multiplicative scale were found only for non-Hispanic Black populations (ratio of RRs, 1.24 [95% CI, 1.18-1.31]) and non-Hispanic White populations (ratio of RRs, 1.03 [95% CI, 1.02-1.05]), but not for Hispanic populations (ratio of RRs, 0.98 [95% CI, 0.93-1.04]). In the sensitivity analyses using continuous Gini coefficient and social mobility, a positive interaction was observed between higher income inequality and lower social mobility with deaths of despair on both the additive and multiplicative scales for all 3 racial and ethnic groups. This cross-sectional study found that the joint exposure of unequal income distribution and lack of social mobility was associated with additional risks for deaths of despair, suggesting that addressing the underlying social and economic conditions is crucial in responding to the epidemic of deaths of despair.