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Related Concept Videos

Primary Healthcare Services01:30

Primary Healthcare Services

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Primary care promotes wellness and prevents disease. This care includes health promotion, education, protection (such as immunizations), early disease screening, and environmental considerations. Settings providing this type of healthcare include physician offices, public health clinics, school nursing, and community health nursing.
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Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
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Preventive Healthcare Services01:30

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Preventive healthcare services keep people healthy via frequent check-ups, screening, and counseling. They primarily aid in disease prevention rather than treating an acute or chronic illness. Preventive treatment also keeps individuals productive and energetic, allowing them to work well into their retirement years. Examples of preventive care services include:
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Principles of Disease Surveillance

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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Healthcare Agencies II01:17

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There are various healthcare agencies in the United States—some of which are managed by religious institutions and others by different government branches.
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At the different levels of the healthcare system, we see varying methods of healthcare used. These methods include managed care systems, case management, and primary healthcare.
Managed Care System:
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Public Health.

Daniel Arnold1, João Pedro Ferrari-Souza2, Rodrigo C Barros3

  • 1Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.

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|December 23, 2025
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Summary
This summary is machine-generated.

This study identified key modifiable risk factors for dementia conversion, including hearing loss and hypertension, alongside non-modifiable factors like age. Machine learning models improve dementia prediction by considering multiple risk factors simultaneously.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Public Health

Background:

  • Dementia risk factor identification is crucial for prevention strategies.
  • Older adults often have multimorbidity, complicating individual risk factor assessment.
  • Simultaneous evaluation of multiple risk factors is needed for accurate dementia prediction.

Purpose of the Study:

  • To simultaneously identify modifiable and non-modifiable risk factors for predicting dementia conversion.
  • To leverage machine learning for comprehensive risk assessment in dementia prediction.
  • To inform dementia prevention strategies by understanding combined risk factor impacts.

Main Methods:

  • Analysis of longitudinal real-world data from the National Alzheimer's Coordinating Center (NACC) (2005-2023).
  • Inclusion of 11 modifiable risk factors (e.g., hearing loss, hypertension, BMI, depression) and 2 non-modifiable factors (age, gender).
  • Application of a machine learning approach, including SHAP value analysis, for simultaneous risk factor evaluation.

Main Results:

  • 11,107 cognitively unimpaired individuals were analyzed, with 1,052 converting to dementia.
  • Machine learning model achieved 66.03% accuracy in predicting dementia conversion (ROC-AUC of 0.745).
  • Age was the most impactful predictor, followed by modifiable factors: hearing loss, hypertension, BMI, depression, visual loss, and education.

Conclusions:

  • Simultaneous evaluation of dementia risk factors, including multimorbidities, is significant for prevention.
  • Hearing loss and hypertension are critical modifiable risk factors alongside age.
  • The machine learning framework offers enhanced predictive accuracy and insights for dementia prevention.