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Purpose: To provide details of a pooled data set that will be used to estimate absolute and relative mortality risks and other outcomes among children less than 59 months of age and the predictive performance of common risk exposures, both individually and in combination.
Participants: Children from birth to 5 years of age recruited at health facilities or community settings into 33 longitudinal observational or intervention studies in 17 low- and middle-income countries.
Findings To Date: The data set includes 75 287 children with a median age of 3 months (IQR 1-12) at first measurement. In the pooled sample, 2805 (3.7%) of the study children died. Data on birth weight was recorded in 19 studies, and gestational age in 13 studies. Among these, 14% of the included children were reported as having low birth weight, and 14% had preterm birth. At first measurement, 33% of the children were stunted, 24% were wasted and 35% underweight. 13% and 7% of caregivers reported that their child had acute diarrhoea or acute lower respiratory tract infection before the study visit, respectively. The proportion of children reported as breastfed at any study visit decreased from 99% at age <6 months to 77% in the age group 12-23 months. Child characteristics differed considerably between studies in the community and healthcare settings. The median study period was 15 months (IQR 7.6-18.4 months).
Future Plans: Planned analyses will examine knowledge gaps with the aim of informing global guidelines and their derivatives such as clinical management tools and implementation guidance, and to inform future research agendas. We aim to estimate absolute mortality risks associated with child age, anthropometry, birth characteristics and feeding practices as planned by the WHO-Risk Stratification Working Group. In the future, other data sets may be added and further questions on survival and growth will be investigated.
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http://dx.doi.org/10.1136/bmjopen-2024-085164 | DOI Listing |
Chaos
September 2025
School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Although many real-world time series are complex, developing methods that can learn from their behavior effectively enough to enable reliable forecasting remains challenging. Recently, several machine-learning approaches have shown promise in addressing this problem. In particular, the echo state network (ESN) architecture, a type of recurrent neural network where neurons are randomly connected and only the read-out layer is trained, has been proposed as suitable for many-step-ahead forecasting tasks.
View Article and Find Full Text PDFAust J Rural Health
October 2025
AgHealth Australia, School of Rural Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
Objective: To describe the pattern and estimated direct economic burdens associated with unintentional deaths and injuries on Australian farms over the past 11 years (2013-2023).
Design: Descriptive retrospective epidemiological study of National Coronial Information System (NCIS) data for persons fatally injured on a farm and workers' compensation injuries data from the National Data Set.
Setting: Australia.
Alzheimers Dement
September 2025
Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Introduction: We compared and measured alignment between the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard used by electronic health records (EHRs), the Clinical Data Interchange Standards Consortium (CDISC) standards used by industry, and the Uniform Data Set (UDS) used by the Alzheimer's Disease Research Centers (ADRCs).
Methods: The ADRC UDS, consisting of 5959 data elements across eleven packets, was mapped to FHIR and CDISC standards by two independent mappers, with discrepancies adjudicated by experts.
Results: Forty-five percent of the 5959 UDS data elements mapped to the FHIR standard, indicating possible electronic obtainment from EHRs.
Most of the United States (US) population resides in cities, where they are subjected to the urban heat island effect. In this study, we develop a method to estimate hourly air temperatures at resolution, improving exposure assessment of US population when compared to existing gridded products. We use an extensive network of personal weather stations to capture the intra-urban variability.
View Article and Find Full Text PDFArch Toxicol
September 2025
Norwegian Scientific Committee for Food and Environment, Norwegian Institute of Public Health, Oslo, Norway.
The transition from traditional animal-based approaches and assessments to New Approach Methodologies (NAMs) marks a scientific revolution in regulatory toxicology, with the potential of enhancing human and environmental protection. However, implementing the effective use of NAMs in regulatory toxicology has proven to be challenging, and so far, efforts to facilitate this change frequently focus on singular technical, psychological or economic inhibitors. This article takes a system-thinking approach to these challenges, a holistic framework for describing interactive relationships between the components of a system of interest.
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