Health risk behaviors practiced during adolescence often persist into adulthood and contribute to the leading causes of morbidity and mortality in the United States. Youth health behavior data at the national, state, territorial, tribal, and local levels help monitor the effectiveness of public health interventions designed to promote adolescent health. The Youth Risk Behavior Surveillance System (YRBSS) is the largest public health surveillance system in the United States, monitoring a broad range of health-related behaviors among high school students. YRBSS includes a nationally representative Youth Risk Behavior Survey (YRBS) and separate state, local school district, territorial, and tribal school-based YRBSs. This overview report describes the surveillance system and the 2019 survey methodology, including sampling, data collection procedures, response rates, data processing, weighting, and analyses presented in this MMWR Supplement. A 2019 YRBS participation map, survey response rates, and student demographic characteristics are included. In 2019, a total of 78 YRBSs were administered to high school student populations across the United States (national and 44 states, 28 local school districts, three territories, and two tribal governments), the greatest number of participating sites with representative data since the surveillance system was established in 1991. The nine reports in this MMWR Supplement are based on national YRBS data collected during August 2018-June 2019. A full description of 2019 YRBS results and downloadable data are available (https://www.cdc.gov/healthyyouth/data/yrbs/index.htm).Efforts to improve YRBSS and related data are ongoing and include updating reliability testing for the national questionnaire, transitioning to electronic survey administration (e.g., pilot testing for a tablet platform), and exploring innovative analytic methods to stratify data by school-level socioeconomic status and geographic location. Stakeholders and public health practitioners can use YRBS data (comparable across national, state, tribal, territorial, and local jurisdictions) to estimate the prevalence of health-related behaviors among different student groups, identify student risk behaviors, monitor health behavior trends, guide public health interventions, and track progress toward national health objectives.
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http://dx.doi.org/10.15585/mmwr.su6901a1 | DOI Listing |
Ann Intern Med
January 2025
Durham VA Health Care System, Durham; and Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina (K.M.G.).
Background: Tissue-based genomic classifiers (GCs) have been developed to improve prostate cancer (PCa) risk assessment and treatment recommendations.
Purpose: To summarize the impact of the Decipher, Oncotype DX Genomic Prostate Score (GPS), and Prolaris GCs on risk stratification and patient-clinician decisions on treatment choice among patients with localized PCa considering first-line treatment.
Data Sources: MEDLINE, EMBASE, and Web of Science published from January 2010 to August 2024.
J Med Internet Res
January 2025
School of Computer Science, University of Technology Sydney, Sydney, Australia.
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication.
View Article and Find Full Text PDFGac Med Mex
January 2025
Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, United Kingdom.
FRAX, a risk calculator that provides individualized 10-year probabilities of hip and major osteoporotic fracture, has been widely used for fracture risk assessment since its launch in 2008. It is now incorporated into very many guidelines worldwide to inform osteoporosis management. In this review, we explore the development of FRAX and how it enhances fracture risk prediction as compared to use of bone mineral density alone, as well as approaches to utilizing FRAX in determining intervention and assessment thresholds.
View Article and Find Full Text PDFJ Infect Dev Ctries
December 2024
SACIDS Africa Centre of Excellence for Infectious Diseases, SACIDS Foundation for One Health, Sokoine University of Agriculture (SUA), P.O. Box 3297 Chuo Kikuu, Morogoro, Tanzania.
Introduction: Peste des petits ruminants (PPR) is an infectious disease that imposes substantial economic burdens on small ruminants (SR) production. For Tanzania to develop efficient management and eradication plans, it is essential to comprehend the seroprevalence of PPR designated for global elimination by 2030.
Methodology: This study investigated the prevalence of PPR in animals kept under pastoral and agropastoral communities in Tanzania.
J Infect Dev Ctries
December 2024
Instituto Nacional de Salud Pública (INSP), Centro de Investigación Sobre Enfermedades Infecciosas (CISEI), Departamento de Diagnóstico Epidemiológico. Cuernavaca, Morelos, México.
Introduction: Escherichia coli has emerged as an important pathogen in urinary tract infections (UTIs) due to the rapid acquisition of antibiotic resistance genes. This enhances the ability of E. coli to colonize and creates therapeutic challenges within the healthcare system.
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