Epidemiological Research Research Articles

Towards advancing Out-of-Hospital cardiac arrest (OHCA) registries globally: Considerations from the global OHCA registry (GOHCAR) collaborative

A growing number out-of-hospital cardiac arrest (OHCA) registries have been developed across the globe. A few of these are national, while others cover larger geographical regions. These registries have common objectives; continuous quality improvement, epidemiological research and providing infrastructure for clinical trials. OHCA registries make performance comparison across Emergency Medical Services systems possible for benchmarking, hypothesis generation and further research. Changes in OHCA incidence and outcomes provide insights about the effects of secular trends or health services interventions. These registries, therefore, have become a mainstay of OHCA management and research. However, developing and maintaining these registries is challenging. Coordination of different service providers to support data collection, sustainable resourcing, data quality and data security are the key challenges faced by these registries.Despite all these challenges, noteworthy progress has been made and further standardization and co-ordination across registries can result in great international benefit. In this paper we present a ‘why’ and ‘how to’ model for setting up OHCA registries, and suggestions for better international co-ordination through a Global OHCA Registries Collaborative (GOHCAR). We draw together the knowledge of a cohort of international researchers, with experience and expertise in OHCA registry development, management, and data synthesis.

Increases in drug-related infant mortality in the United States.

We explored temporal trends in drug-related infant deaths in the United States (U.S.) from 2018 to 2022. We used data from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (WONDER). A total of 295 drug-involved infant deaths were identified from 2018 to 2022 (provisional mortality data for year 2022) based on the underlying cause of death. In the U.S. from 2018 to 2022, there was a significant 2.2-fold increase in drug-involved infant mortality. The observed increases were higher in non-Hispanic White and Black infants. The findings show that drug-involved infant deaths were more likely to occur in the postneonatal period, defined as ages 28-364days (81.4 %) compared to the neonatal period. The most prevalent underlying causes of death included assault (homicide) by drugs, medicaments and biological substances (35.6 %) followed by poisoning dueto exposure to narcotics and psychodysleptics (hallucinogens) (15.6 %). The most common multiple causes of drug-involved infant deaths were psychostimulants with abuse potential of synthetic narcotics. Drug-related infant mortality has increased significantly from 2018 to 2022. These increases are particularly evident among White and Black infants and occurred predominantly in the postneonatal period. These findings require more research but also indicate the need to address drug-involved infant deaths as preventable clinical and public health issues. Effective strategies to reduce drug-involved infant deaths will require preventing and treating maternal substance use disorders, enhancing prenatal care access, and addressing broader social and behavioral risk factors among vulnerable maternal and infant populations.

Geospatial Artificial Intelligence for Estimating Daytime and Nighttime Nitrogen Dioxide Concentration Variations in Taiwan: A Spatial Prediction Model

Nitrogen dioxide (NO2) is a major air pollutant primarily emitted from traffic and industrial activities, posing health risks. However, current air pollution models often underestimate exposure risks by neglecting the bimodal pattern of NO2 levels throughout the day. This study aimed to address this gap by developing ensemble mixed spatial models (EMSM) using geo-artificial intelligence (Geo-AI) to examine the spatial and temporal variations of NO2 concentrations at a high resolution of 50m. These EMSMs integrated spatial modelling methods, including kriging, land use regression, machine learning, and ensemble learning. The models utilized 26 years of observed NO2 measurements, meteorological parameters, geospatial layers, and social and season-dependent variables as representative of emission sources. Separate models were developed for daytime and nighttime periods, which achieved high reliability with adjusted R2 values of 0.92 and 0.93, respectively. The study revealed that mean NO2 concentrations were significantly higher at nighttime (9.60 ppb) compared to daytime (5.61 ppb). Additionally, winter exhibited the highest NO2 levels regardless of time period. The developed EMSMs were utilized to generate maps illustrating NO2 levels pre and during COVID restrictions in Taiwan. These findings could aid epidemiological research on exposure risks and support policy-making and environmental planning initiatives.

Integrating the Patient's Voice into the Research Agenda for Treatment of Chemosensory Disorders.

World-wide some 658 million people were infected with COVID-19 and millions suffer from chemosensory impairment associated with long COVID. Current treatments for taste and smell disorders are limited. Involving patients has the potential to catalyze the dynamic exchange and development of new ideas and approaches to facilitate biomedical research and therapeutics. We assessed patients' perceptions of the efficacy of treatments for chemosensory impairment using an online questionnaire completed by 5,815 people in the U.S. Logistic regression determined variables predictive of reported treatment efficacy for patients aged 18-24, 25-39, 40-60 and 60+ yrs. who were treated with nasal steroids, oral steroids, zinc, nasal rinse, smell training, theophylline, platelet rich plasma, and Omega 3. The most consistent predictor was age, with the majority of those 40-60 and 60+ reporting that nasal steroids, oral steroids, zinc, nasal rinse and smell training were only slightly effective or not effective at all. Many of these treatment strategies target regeneration and immune response, processes compromised by age. Only those under 40 reported more than slight efficacy of steroids or smell training. Findings emphasize the need to include patients of all ages in clinical trials. Older adults with olfactory impairment are at increased risk for Alzheimer's disease (AD). We speculate that olfactory impairment associated with long COVID introduces the potential for a significant rise in AD. Long COVID-associated chemosensory impairment increases the urgency for translational and clinical research on novel treatment strategies. Suggestions for high priority areas for epidemiological, basic, and clinical research on chemosensory impairment follow.

Abstract B001: Urinary bladder cancer incidence and mortality in the United States: 20-year trends and initial impact of the COVID-19 pandemic

Abstract Introduction: We examined nationwide trends in urinary bladder cancer incidence and mortality focusing on 1999-2019. A separate analysis of data from 2020 revealed how these rates were affected by the onset of the COVID-19 pandemic. Methods: State-specific bladder cancer (in situ and invasive) incidence and mortality rates were ascertained from the United States (US) Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) database for 1999-2020 overall and according to age, gender, and geographic region. All rates were age-adjusted to the 2000 US Census population, except age-specific rates. We used Joinpoint software to calculate the 20-year average annual percent change and annual percent change for specific periods identified by data-driven joinpoint placement with 95% confidence intervals (CI). Results: In 2019, the US bladder cancer incidence rate was 18.8 (CI, 18.6 to 18.9) cases per 100,000. Bladder cancer incidence decreased 0.9% annually (CI, 0.8 to 1.0% decrease) during 1999-2019, with a 3.3% annual decrease (CI, 2.5 to 4.1% decrease) during 2016-2019 specifically. Among men, the 20-year annual decrease was 1.1% (CI, 1.0 to 1.1% decrease), with a 3.8% annual decrease (CI, 2.8 to 4.6% decrease) during 2017-2019 specifically. Among women, the 20-year annual decrease was 1.0% (CI, 0.9 to 1.2% decrease), with a 2.6% annual decrease (CI, 1.7 to 4.2% decrease) during 2016-2019 specifically. Largest annual decreases in incidence rates were seen among 55-59-year-olds (1.8%, CI, 1.6 to 2.0% decrease), and in the western US (2.3%, CI, 2.0 to 2.6% decrease). Conversely, some southern states showed an increase in incidence. In Tennessee, there was a 20-year annual increase of 1.2% (CI, 0.9 to 1.6% increase). In 2019, the US bladder cancer mortality rate was 4.1 (CI, 4.0 to 4.2) deaths per 100,000. Bladder cancer mortality decreased 0.4% annually (CI, 0.2 to 0.5% decrease) during 1999-2019, with a 2.5% annual decrease (CI, 1.3 to 4.7% decrease) during 2016-2019 specifically. Mortality rate trends were generally similar among men and women (0.4% and 0.7% decrease annually, respectively). Largest annual decreases in mortality rates were seen among 50-54-year-olds (1.5%, CI, 0.6 to 2.4% decrease) and in the northeast US (0.8%, CI, 0.7 to 1.0% decrease). Reflecting the initial impact of the COVID-19 pandemic, bladder cancer incidence decreased by 8.6% (CI, 7.7 to 9.6% decrease) and bladder cancer mortality decreased by 2.7% (CI, 0.6 to 4.8% decrease) comparing 2020 with 2019. Conclusions: After decades remaining relatively constant, bladder cancer incidence and mortality rates in the US began to decrease around 2016-2017. This trend was less apparent in the southern part of the country, where incidence trended upward in some states. As evident for other common cancers, bladder cancer incidence rates decreased sharply during the first year of the COVID-19 pandemic. Forthcoming data for 2021-2024 will provide a clearer picture of the magnitude of this disruption and the possibility of a rebound. Citation Format: Grace B. Gallant, Hugo Pomares-Millan, Judy R. Rees, Margaret R. Karagas, Michael N. Passarelli. Urinary bladder cancer incidence and mortality in the United States: 20-year trends and initial impact of the COVID-19 pandemic [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr B001.

It's not all about residual confounding: a plea for QBA for epidemiologic researchers and educators.

We spend a great deal of time on confounding in our teaching, in our methods development and in our assessment of study results. This may give the impression that uncontrolled confounding is the biggest problem that observational epidemiology faces, when in fact, other sources of bias such as selection bias, measurement error, missing data, and misalignment of zero time may often (especially if they are all present in a single study) lead to a stronger deviation from the truth. Compared to the amount of time we spend teaching how to address confounding in a data analysis, we spend relatively little time teaching methods for simulating confounding (and other sources of bias) to learn their impact and develop plans to mitigate or quantify the bias. We review a paper by Desai et al that uses simulation methods to quantify the impact of an unmeasured confounder when it is completely missing or when a proxy of the confounder is measured. We use this article to discuss how we can use simulations of sources of bias to ensure we generate better and more valid study estimates, and we discuss the importance of simulating realistic datasets with plausible bias structures to guide data collection. If an advanced life form exists outside of our current universe and they came to earth with the goal of scouring the published epidemiologic literature to understand what the biggest problem epidemiologists have, they would quickly discover that the limitations section of publications would provide them with all the information they needed. And most likely what they would conclude is that the biggest problem that we face is uncontrolled confounding. It seems to be an obsession of ours.

A Carbon Monoxide Poisoning Case Insight: The Convergence of Social Media and Epidemiology

This study explores the role of social media in public health through a case of carbon monoxide (CO) poisoning prevented and subsequently overlooked, as influenced by digital community interaction. A TikTok influencer shared an experience with a coal stove, leading to followers advising against its use due to CO poisoning risks. This advice was heeded, yet a family member, unaware of these risks, experienced CO poisoning. This incident illuminates social media’s potential in disseminating life-saving health information and influencing behavior, forming the basis of “Media Epidemiology.” This new field studies how digital communication impacts health-related behaviors and outcomes. Our analysis highlights social media as a tool for rapid health information dissemination and preventive action. It underscores the need for integrating digital platform dynamics into public health strategies, emphasizing education on hazards like CO poisoning. This study advocates for leveraging social media in public health, exemplifying its role in disease prevention and health promotion, and marking a significant stride in contemporary epidemiological research.

Invited Commentary: Mixing multiple imputation and bootstrapping for variance estimation.

In 2023, Martinez et al. examined trends in the inclusion, conceptualization, operationalization and analysis of race and ethnicity among studies published in US epidemiology journals. Based on a random sample of papers (N=1,050) published from 1995-2018, the authors describe the treatment of race, ethnicity, and ethnorace in the analytic sample (N=414, 39% of baseline sample) over time. Between 32% and 19% of studies in each time stratum lacked race data; 61% to 34% lacked ethnicity data. The review supplies stark evidence of the routine omission and variability of measures of race and ethnicity in epidemiologic research. Informed by public health critical race praxis (PHCRP), this commentary discusses the implications of four problems the findings suggest pervade epidemiology: 1) a general lack of clarity about what race and ethnicity are; 2) the limited use of critical race or other theory; 3) an ironic lack of rigor in measuring race and ethnicity; and, 4) the ordinariness of racism and white supremacy in epidemiology. The identified practices reflect neither current publication guidelines nor the state of the knowledge on race, ethnicity and racism; therefore, we conclude by offering recommendations to move epidemiology toward more rigorous research in an increasingly diverse society.

Multimorbidity patterns and trajectories in young and middle-aged adults: a large-scale population-based cohort study

IntroductionThe presence of multiple chronic conditions, also referred to as multimorbidity, is a common finding in adults. Epidemiologic research can help identify groups of individuals with similar clinical profiles who could benefit from similar interventions. Many cross-sectional studies have revealed the existence of different multimorbidity patterns. Most of these studies were focused on the older population. However, multimorbidity patterns begin to form at a young age and can evolve over time following distinct multimorbidity trajectories with different impact on health. In this study, we aimed to identify multimorbidity patterns and trajectories in adults 18–65 years old.MethodsWe conducted a retrospective longitudinal epidemiologic study in the EpiChron Cohort, which includes all inhabitants of Aragón (Spain) registered as users of the Spanish National Health System, linking, at the patient level, information from electronic health records from both primary and specialised care. We included all 293,923 patients 18–65 years old with multimorbidity in 2011. We used cluster analysis at baseline (2011) and in 2015 and 2019 to identify multimorbidity patterns at four and eight years of follow-up, and we then created alluvial plots to visualise multimorbidity trajectories. We performed age- and sex-adjusted logistic regression analysis to study the association of each pattern with four- and eight-year mortality.ResultsWe identified three multimorbidity patterns at baseline, named dyslipidaemia & endocrine-metabolic, hypertension & obesity, and unspecific. The hypertension & obesity pattern, found in one out of every four patients was associated with a higher likelihood of four- and eight-year mortality (age- and sex-adjusted odds ratio 1.11 and 1.16, respectively) compared to the unspecific pattern. Baseline patterns evolved into different patterns during the follow-up.DiscussionWell-known preventable cardiovascular risk factors were key elements in most patterns, highlighting the role of hypertension and obesity as risk factors for higher mortality. Two out of every three patients had a cardiovascular profile with chronic conditions like diabetes and obesity that are linked to low-grade systemic chronic inflammation. More studies are encouraged to better characterise the relatively large portion of the population with an unspecific disease pattern and to help design and implement effective and comprehensive strategies towards healthier ageing.

Racial/ethnic trends in opioid and polysubstance opioid overdose mortality in adolescents and young adults, 1999–2020

ObjectivesPrevious reports have described variations in opioid overdose mortalities among different race/ethnicity groups. We have analyzed racial/ethnicity trends in opioid and polysubstance opioid overdose mortalities in adolescents and young adults to further characterize differences and potential sub-epidemics within this specific population. MethodsWe used mortality data from the U.S. Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (WONDER) Multiple Cause of Death file from 1999 to 2020. Drug overdose mortalities were identified using International Classification of Diseases, Tenth Revision (ICD-10) codes. Joinpoint regression was used to examine mortality rates for all opioids, opioids with a stimulant, opioids with benzodiazepines, and opioids with alcohol among racial/ethnic groups (non-Hispanic white, non-Hispanic Black, Hispanic, non-Hispanic other) in adolescents and young adults. ResultsThe Average Annual Percent Change (AAPC) for mortality due to opioid and polysubstance opioid overdose increased for all racial/ethnic groups where data was available for analysis from 1999 to 2020. For mortality due to any opioid and any opioid with a stimulant, the greatest AAPC was seen among non-Hispanic Blacks. ConclusionsUnprecedented increases in mortality due to opioid overdose occurred in the last two decades among adolescents and young adults. Heterogenous trends support the notion that the previously defined opioid overdose epidemic “waves” may not accurately depict the effects of the crisis in all race/ethnicity groups. Additionally, alarming increases in opioid-stimulant overdose mortality starting in 2012 further characterize the interrelated effects of the third and fourth waves.

Passive and active field theories for disease spreading

Abstract The worldwide COVID-19 pandemic has led to a significant growth of interest in the development of mathematical models that allow to describe effects such as social distancing measures, the development of vaccines, and mutations. Several of these models are based on concepts from soft matter theory. Considerably less well investigated is the reverse direction, i.e., how results from epidemiological research can be of interest for the physics of colloids and polymers. In this work, we consider the SIR-DDFT model, a combination of the susceptible-infected-recovered (SIR) model from epidemiology with dynamical density functional theory (DDFT) from nonequilibrium soft matter physics, which allows for an explicit modeling of social distancing. We extend the SIR-DDFT model both from an epidemiological perspective by incorporating vaccines, asymptomaticity, reinfections, and mutations, and from a soft matter perspective by incorporating noise and self-propulsion and by deriving a phase field crystal (PFC) model that allows for a simplified description. On this basis, we investigate via computer simulations how epidemiological models are affected by the presence of non-reciprocal interactions. This is done in a numerical study of a zombie outbreak.

The American College of Rheumatology White Paper: The Effects of Climate Change on Rheumatic Conditions - An Evolving Landscape and a Path Forward.

Increases in global temperatures and extreme weather events associated with climate change have complex yet poorly understood detrimental impacts on human health. We reviewed the current published literature on climate change-related effects and rheumatic conditions. To summarize our current understanding of the likely effects of climate change, including increased air pollution, on rheumatic disease, we searched the published, peer-reviewed English-language literature from January 2000-December 2022. Articles were reviewed by a team of rheumatologists and clinical and translational science researchers. Systematic review articles were not included but informed additional literature searches. After extensive examination and adjudication, 88 articles met inclusion criteria and were selected for review. Much of the epidemiologic investigations assessed associations between air pollution and increased risk of development of rheumatoid arthritis, anti-citrullinated protein antibodies, flares of gout and hospitalizations for systemic lupus erythematosus. Increased heat vulnerability was associated with higher odds of recurrent hospitalizations across rheumatic conditions. Mechanisms for observed associations are poorly understood but could include the effects of epigenetic changes, oxidative stress, and inflammatory cytokines. Studies had limitations including restricted geography and populations studied without focus on historically marginalized communities at highest risk for adverse effects from pollution and climate change, the relative lack of mechanistic evaluations, and most with only indirect links to climate change. To date, the published literature lacks studies that directly examine effects of climate change on rheumatic diseases. Collaborative translational and epidemiologic research is needed to enhance our understanding and awareness in this area.

Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure.

Inter-individual variation in blood pressure (BP) arises in part from sequence variants within enhancers modulating the expression of causal genes. We propose that these genes, active in tissues relevant to BP physiology, can be identified from tissue-level epigenomic data and genotypes of BP-phenotyped individuals. We used chromatin accessibility data from the heart, adrenal, kidney, and artery to identify cis-regulatory elements (CREs) in these tissues and estimate the impact of common human single-nucleotide variants within these CREs on gene expression, using machine learning methods. To identify causal genes, we performed a gene-wise association test. We conducted analyses in 2 separate large-scale cohorts: 77 822 individuals from the Genetic Epidemiology Research on Adult Health and Aging and 315 270 individuals from the UK Biobank. We identified 309, 259, 331, and 367 genes (false discovery rate <0.05) for diastolic BP and 191, 184, 204, and 204 genes for systolic BP in the artery, kidney, heart, and adrenal, respectively, in Genetic Epidemiology Research on Adult Health and Aging; 50% to 70% of these genes were replicated in the UK Biobank, significantly higher than the 12% to 15% expected by chance (P<0.0001). These results enabled tissue expression prediction of these 988 to 2875 putative BP genes in individuals of both cohorts to construct an expression polygenic score. This score explained ≈27% of the reported single-nucleotide variant heritability, substantially higher than expected from prior studies. Our work demonstrates the power of tissue-restricted comprehensive CRE analysis, followed by CRE-based expression prediction, for understanding BP regulation in relevant tissues and provides dual-modality supporting evidence, CRE and expression, for the causality genes.

Neuromyelitis optica spectrum disorders registry system in Iran: Validity of data sets

BackgroundA targeted structure for recording, monitoring, and follow-up of patients with neuromyelitis optica spectrum disorders (NMOSD) is in demand. To obtain the correct and uniform standardized information registry system, it is necessary to use a data set that has good validity to help policy-makers systematically plan for improvements in the quality of care. The main goal of the present study was to develop a NMOSD data set for the national registry system in Iran (NMORI) and to evaluate the validity of the presented data set. MethodsThe NMORI data set consisted of baseline characteristics, disease and exposure history, background and past medical history, diagnosis and treatment, clinical features, imaging, and para-clinical findings. The content validity was evaluated by 18 experts from Iran, Japan, and Denmark by scoring each of the questionnaire items in term of transparency, simplicity, and relevance. According to the points given, the content validity index (CVI) and content validity ratio (CVR) scores were calculated and compared with the critical limit. ResultsThe current study was designed as a 125-items data set which was considered valid. In terms of relevance 110 out of 125 items, simplicity 113 out of 125 items, and transparency 123 out of 125 items had Item-CVI>0.79. All Scale-level-CVI values were greater than 0.9, showing noticeable content validity. In this data set, 112 items had CVR > 0.49, which was considered an acceptable level of significance. ConclusionThe implementing of NMORI is important in a developing country such as Iran with significant increasing prevalence of this disease. This registry facilitates a uniform and valid diagnosis and is considered valid for clinical investigation and epidemiological research on NMOSD. Scientists and healthcare policymakers can rely on a validated data set in order to have access to accurate data.

In Vitro and In Vivo Biotransformation Profiling of 6PPD-Quinone toward Their Detection in Human Urine.

The antioxidant N-(1,3-Dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its oxidized quinone product 6PPD-quinone (6PPD-Q) in rubber have attracted attention due to the ecological risk that they pose. Both 6PPD and 6PPD-Q have been detected in various environments that humans cohabit. However, to date, a clear understanding of the biotransformation of 6PPD-Q and a potential biomarker for exposure in humans are lacking. To address this issue, this study presents a comprehensive analysis of the extensive biotransformation of 6PPD-Q across species, encompassing both in vitro and in vivo models. We have tentatively identified 17 biotransformation metabolites in vitro, 15 in mice in vivo, and confirmed the presence of two metabolites in human urine samples. Interestingly, different biotransformation patterns were observed across species. Through semiquantitative analysis based on peak areas, we found that almost all 6PPD-Q underwent biotransformation within 24 h of exposure in mice, primarily via hydroxylation and subsequent glucuronidation. This suggests a rapid metabolic processing of 6PPD-Q in mammals, underscoring the importance of identifying effective biomarkers for exposure. Notably, monohydroxy 6PPD-Q and 6PPD-Q-O-glucuronide were consistently the most predominant metabolites across our studies, highlighting monohydroxy 6PPD-Q as a potential key biomarker for epidemiological research. These findings represent the first comprehensive data set on 6PPD-Q biotransformation in mammalian systems, offering insights into the metabolic pathways involved and possible exposure biomarkers.

Editorial: Diversity in stroke omic(s) and epidemiology research: opportunities and challenges

Editorial: Diversity in stroke omic(s) and epidemiology research: opportunities and challenges

Perceptions on Indigenous Medicine, First Aid and Treatment of Snakebite among Sri Lankan Farmers

Since snakebite is a serious public health concern in Asia, one of the most affected countries is Sri Lanka. The incidence, species variety, clinical symptoms, and management of snakebite in Asia, with a focus on Sri Lanka, are all covered in this review paper. Many of the venomous snake species found in Asia are abundant and diverse. Snake bites are a typical occurrence, especially in rural areas where farming and encounters between humans and snakes are common. Numerous snake species, including the dangerous Russell’s viper and the spectacled cobra, are found in Sri Lanka specifically. Depending on the type of snake bitten and the amount of venom administered, different clinical symptoms might result from a snake bite. Pain, bruising, swelling, and systemic symptoms like nausea, vomiting, and paralysis are typical ones. Treatment that is given too slowly or not at all can result in fatal consequences. Antivenom delivery, wound care, and supportive measures are all essential components of managing snake bite cases effectively. However, obstacles including a lack of access to medical facilities and less availability of antivenom sometimes make it difficult to get treatment quickly, particularly in isolated places and concern about indigenous treatment as well. Public awareness campaigns, better healthcare facilities, and epidemiology research are only a few of the measures taken against snakebite in Sri Lanka. To lessen the number of snakebites in, government institutions, medical professionals, and international organizations must work together. Better antivenom medicines and improved preventive and treatment plans for snakebite in this area require more study and funding.International Journal of Human and Health Sciences Vol. 08 No. 02 Apr’24 Page: 116-125

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.

Systematic review and meta-analysis of birth weight and perfluorohexane sulfonate exposures: examination of sample timing and study confidence

We examined the association between mean birth weight (BW) differences and perfluorohexane sulfonate (PFHxS) exposure biomarkers.We fit a random effects model to estimate the overall pooled effect and for different...

Review on Childhood Obesity: Discussing Effects of Gestational Age at Birth and Spotting Association of Postterm Birth with Childhood Obesity

Overweight and obesity in children and adolescents and its negative effects on health, including increased risks of long-term diseases like type II DM, CVD, dyslipidemia, , stroke, hypertension, respiratory issues, gallbladder disease, sleep apnea, osteoarthritis, along with certain malignancies, which are already identified during the perinatal and prenatal period is one of the most important worldwide health concerns of the twenty-first century. To overcome the current epidemic of overweight and obesity, obstructing their risk factors is important in an effort to prevent the development of obesity and overweight. Multiple epidemiological research studies have shown a connection between BMI acquired later in life and birth weight; however, the results are constrained by the absence of information on gestational age. Majority of studies reported relation of childhood obesity with the preterm born children in study of relation with the gestational age. Although more likely to become obese in later adulthood, preterm and low birth weight born child are small and/or lean at birth, whereas post-term usually not and above all, children born postterm showed signs of a rapid weight gain that led to obesity decades early. Thus, the purpose of this review study is to determine the impact of the gestational age at delivery and to provide an overview of the evidence supporting the link between childhood obesity and post-term birth.. Thorough systemic review conducted on online database Pubmed, Google Scholar and found only few studies on association with the post- term born children. Limited evidence necessitated the studying of additional adult post-term cohorts to accurately determine future risks to health and to investigate these potential metabolic alterations, as well as if the alterations in adiposity continue or get worse throughout adulthood, and how these correlations vary in adult born post-term in terms of pattern and amplitude.