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Related Concept Videos

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Correlation between ECG and Cardiac Cycle01:25

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The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
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Lifestyle Factors and Health01:20

Lifestyle Factors and Health

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Lifestyle factors play a critical role in maintaining overall health and preventing chronic diseases. Key elements, such as regular physical activity, a nutritious diet, and abstinence from smoking, can significantly enhance physical, mental, and emotional well-being while reducing the risk of several life-threatening conditions.
Benefits of Physical Activity
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Dimensions of Health and Illness01:21

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The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.
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Cause and Effect01:53

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While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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Calculating and Interpreting the Linear Correlation Coefficient01:11

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The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:
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Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
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Healthy Behavior and Environmental Behavior Correlate with Bicycle Commuting.

Qiang Liu1,2, Toshiaki Yamada3, Hang Liu4

  • 1Institute of Policy Research, Kumamoto 860-0806, Japan.

International Journal of Environmental Research and Public Health
|March 25, 2022
PubMed
Summary

This study found that avoiding tobacco or overdrinking, engaging in physical activity, and making eco-conscious purchasing choices positively correlate with choosing bicycle commuting. These healthy and environmental behaviors influence sustainable transportation choices.

Keywords:
bicycle commutingbinary logistic regressionenvironmental behaviorfactor analysishealthy behavior

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Area of Science:

  • Environmental Psychology
  • Public Health
  • Sustainable Transportation

Background:

  • Environmental awareness is linked to bicycle travel.
  • Limited research explores connections between healthy/environmental behaviors and cycling.

Purpose of the Study:

  • To investigate the relationship between various healthy and environmental behaviors and bicycle commuting.
  • To identify specific behaviors that encourage cycling.

Main Methods:

  • Survey data from 803 residents.
  • Factor analysis to identify latent factors of healthy and environmental behaviors.
  • Binary logistic regression to analyze the relationship with cycling usage.

Main Results:

  • Three healthy behavior factors: healthy diet, avoiding tobacco/overdrinking, physical activity.
  • Two environmental behavior factors: household behavior, purchasing behavior.
  • Avoiding tobacco/overdrinking, physical activity, and purchasing behavior positively correlated with bicycle commuting.

Conclusions:

  • Specific healthy behaviors (avoiding tobacco/overdrinking, physical activity) and environmental behaviors (purchasing behavior) are significant predictors of bicycle commuting.
  • Findings highlight the multifaceted nature of sustainable transport choices, influenced by lifestyle and environmental consciousness.