The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus ignoring the changing population densities resulting from human mobility. Existing assessments of spatio-temporal population are limited in their detail and geographical coverage, and the promising mobile-phone records are hindered by issues concerning availability and consistency. Here, we present a multi-layered dasymetric approach that combines official statistics with geospatial data from emerging sources to produce and validate a European Union-wide dataset of population grids taking into account intraday and monthly population variations at 1 km resolution. The results reproduce and systematically quantify known insights concerning the spatio-temporal population density structure of large European cities, whose daytime population we estimate to be, on average, 1.9 times higher than night time in city centers.
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http://dx.doi.org/10.1038/s41467-020-18344-5 | DOI Listing |
Arch Gerontol Geriatr
January 2025
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, Singapore 117549, Singapore. Electronic address:
Background: Both air pollution and low socioeconomic status (SES) are associated with worse cognitive function. The extent to which low SES may compound the adverse effect of air pollution on cognitive function remains unclear.
Methods: 7,087 older adults aged 65 and above were included from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and followed up in 4 waves during 2008-2018.
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 PDFJ Particip Med
January 2025
Division of Allergy & Pulmonary Medicine, Washington University School of Medicine, St Louis, MO, United States.
Background: Adolescents and young adults (AYA) with cystic fibrosis (CF) are at risk for deviating from their daily treatment regimen due to significant time burden, complicated daily therapies, and life stressors. Developing patient-centric, effective, engaging, and practical behavioral interventions is vital to help sustain therapeutically meaningful self-management.
Objective: This study aimed to devise and refine a patient-centered telecoaching intervention to foster self-management in AYA with CF using a combination of intervention development approaches, including an evidence- and theory-based approach (ie, applying existing theories and research evidence for behavior change) and a target population-centered approach (ie, intervention refinement based on the perspectives and actions of those individuals who will use it).
JMIR Ment Health
January 2025
Division of Psychology and Mental Health, University of Manchester, Manchester, United Kingdom.
Background: Digital mental health interventions (DMHIs) to monitor and improve the health of people with psychosis or bipolar disorder show promise; however, user engagement is variable, and integrated clinical use is low.
Objective: This prospectively registered systematic review examined barriers and facilitators of clinician and patient engagement with DMHIs, to inform implementation within real-world settings.
Methods: A systematic search of 7 databases identified empirical studies reporting qualitative or quantitative data about factors affecting staff or patient engagement with DMHIs aiming to monitor or improve the mental or physical health of people with psychosis or bipolar disorder.
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