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Related Concept Videos

Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Structural Joints: Fibrous Joints01:03

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
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Joints01:26

Joints

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Joints, also called articulations or articular surfaces, are points at which ligaments or other tissues connect adjacent bones. Joints permit movement and stability, and can be classified based on their structure or function.
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Fibrous Joints Are Immovable
The bones of a...
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Theory of Attribution II: Kelley's Covariation Theory01:29

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Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus:...
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Models of Health Promotion and Illness Prevention II01:18

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The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
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JOINT MEAN AND COVARIANCE MODELING OF MULTIPLE HEALTH OUTCOME MEASURES.

Xiaoyue Niu1, Peter D Hoff2

  • 1DEPARTMENT OF STATISTICS, PENNSYLVANIA STATE UNIVERSITY, 323C THOMAS BUILDING, UNIVERSITY PARK, PENNSYLVANIA 16802, USA.

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Summary

This study reveals that health reference ranges and disease associations vary across different U.S. subpopulations. Analyzing National Health and Nutrition Examination Survey data, it highlights the need for tailored health assessments.

Keywords:
Heterogeneous populationNHANEScovariance regressionreference range

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Area of Science:

  • Biostatistics
  • Public Health
  • Epidemiology

Background:

  • Health exams rely on population reference ranges, assuming uniformity across diverse groups.
  • Established relationships among health problems are often generalized, potentially overlooking subpopulation variations.

Purpose of the Study:

  • To investigate how health reference ranges and the associations between health outcomes differ across subpopulations in the U.S.
  • To apply a joint statistical model to analyze variations in health data.

Main Methods:

  • Utilized data from the 2009-2010 National Health and Nutrition Examination Survey (NHANES).
  • Employed a joint mean and covariance model to analyze four major health problems.
  • Incorporated model selection criteria like AIC and posterior predictive checks for evaluation.

Main Results:

  • Demonstrated significant variations in health outcome reference ranges and associations among different subpopulations.
  • Identified specific subpopulations where current reference ranges may be inadequate.

Conclusions:

  • Standard health reference ranges may not accurately represent all subpopulations.
  • The proposed statistical model can identify areas needing further data collection to refine health assessments and understand disease associations within specific groups.