The rising global burden of noncommunicable diseases (NCDs) has heightened awareness of the necessity for primary risk prevention programmes. These aim to facilitate long-term behaviour changes in children and adolescents that can reduce NCD risk factors and disease onset in later-life. School-based programmes designed to improve childhood and adolescent health behaviours and wellbeing contribute to this; however, design and impact assessment of these is complex. These programmes should be multidisciplinary, utilizing both educational and health expertise. Health outcomes may not be evident in the short term, but may occur with learning-related behaviour modifications, highly effective when sustained over a lifetime. Thus assessment must analyse short-term learning and behaviour impacts as well as long-term capability, behaviour and health outcomes.The focus of assessment measures in the health and education sectors differs and often lacks depth in one or other area. Educators generally focus on identifying evidence of learning related to capability, attitude and/or behaviour changes, while public health practitioners typically focus on health measures (e.g. body mass index (BMI), mental health, or risk behaviours).We argue that multidisciplinary approaches incorporating education and health viewpoints clarify issues relating to the potential value of schools as a setting to facilitate primary NCD risk reduction. To demonstrate this, we need to: 1) build stronger understandings of the features of effective learning for behavioural change and the best way to evaluate these, and 2) convincingly correlate these measures with long-term metabolic health indicators by tracking learner behaviour and health over time.
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http://dx.doi.org/10.1093/heapro/daw096 | DOI Listing |
Front Glob Womens Health
December 2024
Quality Unit, Sawla General Hospital, Sawla, Ethiopia.
Background: The burden of non-communicable diseases (NCDs) increasing at an alarming rate in Ethiopia. NCDs affect reproductive-age women and cause significant threats to future generations. Screening is an important aspect leading to early diagnosis, treatment and preventing the risk of complications and future mortality.
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January 2025
Sree Chitra Tirunal Institute for Medical Sciences and Technology (SCTIMST), Trivandrum, India.
Survival outcomes of patients with heart failure (HF) based on their disease etiology are not well described. Here, we provide one-year mortality outcomes of 10850 patients with HF (mean age = 59.9 years, 31% women) in India.
View Article and Find Full Text PDFInn Med (Heidelb)
December 2024
Zentrum für Kardiologie, Universitätsmedizin Mainz, Johannes Gutenberg-Universität, Langenbeckstraße 1, 55131, Mainz, Deutschland.
Noncommunicable diseases (NCDs) are responsible for the premature deaths of more than 38 million people each year, making them the leading cause of the global burden of disease, accounting for 70% of global mortality. The majority of these deaths are caused by cardiovascular diseases. The risk of NCDs is closely related to exposure to environmental stressors such as air pollution, noise pollution, artificial light at night, and climate change, including extreme heat, sandstorms, and wildfires.
View Article and Find Full Text PDFIndian J Med Res
November 2024
Department of Community Medicine, Burdwan Medical College & Hospital, Kolkata, West Bengal, India.
Background & objectives Non communicable diseases (NCD) have emerged as one of the leading causes of mortality and morbidity in India in the past few decades. This study was undertaken to determine the prevalence of NCD risk factors among adults residing in urban slums of West Bengal, India. Methods A community based cross-sectional study was conducted among adult population aged 15-69 yr in urban slums of Purba Burdwan district, West Bengal over a period of two months.
View Article and Find Full Text PDFBMC Public Health
December 2024
Upstream Lab, MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
Background: Machine learning (ML) is increasingly used in population and public health to support epidemiological studies, surveillance, and evaluation. Our objective was to conduct a scoping review to identify studies that use ML in population health, with a focus on its use in non-communicable diseases (NCDs). We also examine potential algorithmic biases in model design, training, and implementation, as well as efforts to mitigate these biases.
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