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Related Concept Videos

Factors Affecting Illness01:18

Factors Affecting Illness

When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness, disability,...
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...
Factors Influencing Drug Absorption: Disease States and Pharmacology01:25

Factors Influencing Drug Absorption: Disease States and Pharmacology

Multiple disease states can significantly influence the oral drug absorption process by affecting blood flow and the functionality of the gastrointestinal (GI) system. Various GI diseases, including conditions that alter GI motility, such as diarrhea, decreased acid secretions (achlorhydria), and infections, have been associated with reduced drug absorption.
Substances such as alcohol and specific drugs, including antineoplastics, can also negatively impact drug absorption. For instance,...
Dimensions of Health and Illness01:21

Dimensions of Health and Illness

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.
Factorial Design02:01

Factorial Design

Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
Lifestyle Factors and Health01:20

Lifestyle Factors and Health

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
Physical activity, whether through structured exercise or casual activities like walking, biking, or dancing, is a cornerstone of a...

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Application of Unsupervised Multi-Omic Factor Analysis to Uncover Patterns of Variation and Molecular Processes Linked to Cardiovascular Disease
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Multimorbidity patterns in primary care: interactions among chronic diseases using factor analysis.

Alexandra Prados-Torres1, Beatriz Poblador-Plou, Amaia Calderón-Larrañaga

  • 1IIS Aragón, Aragón Health Sciences Institute, Miguel Servet University Hospital, University of Zaragoza, Zaragoza, Spain.

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Chronic diseases often cluster together, forming distinct multimorbidity patterns that vary by age and sex. Understanding these patterns is key for targeted clinical and public health interventions.

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Area of Science:

  • Epidemiology
  • Public Health
  • Gerontology

Background:

  • Chronic disease multimorbidity is a growing concern in primary care.
  • Identifying distinct patterns of co-occurring diseases is crucial for effective management.
  • Understanding the evolution of these patterns over time and across demographics is essential.

Purpose of the Study:

  • To identify and describe chronic disease multimorbidity patterns in a primary care population.
  • To analyze how these patterns change and evolve with age and sex.
  • To explore the underlying pathophysiological processes and disease interactions in multimorbidity.

Main Methods:

  • Observational, retrospective, multicentre study using electronic medical records.
  • Exploratory factor analysis on diagnostic data from 275,682 patients (age >14).
  • Analysis stratified by age group and sex.

Main Results:

  • Multimorbidity prevalence increases with age, from 13% (15-44 years) to 67% (≥65 years).
  • Five distinct multimorbidity patterns were identified: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric, and depressive.
  • Patterns showed age-related evolution and sex-specific differences.

Conclusions:

  • Non-random chronic disease associations form clinically consistent multimorbidity patterns.
  • These patterns affect a significant population segment and have underlying pathophysiological bases.
  • Findings support targeted clinical and public health interventions for multimorbidity management.