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Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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Obesity01:24

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The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
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Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
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When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
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Observational Studies01:11

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Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
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Updated: Sep 19, 2025

Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
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Exploring obesity phenotypes: a longitudinal perspective.

Ricardo Rosero-Revelo1, Mateo Tamayo2, Ricardo Correa3

  • 1Department of Endocrinology, Diabetes and Metabolism, Cleveland Clinic, Cleveland, OH, USA. roseror@ccf.org.

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This summary is machine-generated.

Body Mass Index (BMI) is insufficient for diagnosing obesity. Comprehensive body composition analysis offers better risk stratification and personalized treatments for obesity, improving health outcomes.

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Area of Science:

  • Obesity Medicine
  • Metabolic Health
  • Body Composition Analysis

Background:

  • Traditional Body Mass Index (BMI) lacks accuracy in differentiating fat from lean mass and assessing fat distribution.
  • Emerging evidence highlights the need for comprehensive body composition evaluation for precise obesity risk stratification.
  • Insights from the 2025 Lancet Commission on Obesity underscore the limitations of current diagnostic tools.

Purpose of the Study:

  • To review the evolution of obesity phenotyping from BMI-based methods to multifaceted approaches.
  • To examine the metabolic, genetic, and hormonal factors contributing to phenotypic variability in obesity.
  • To demonstrate how refined obesity phenotyping can predict disease progression and guide personalized interventions.

Main Methods:

  • Synthesis of historical perspectives and recent developments in obesity phenotyping.
  • Integration of original longitudinal data from Latino patients with obesity.
  • Review of current literature on bioelectrical impedance analysis (BIA) and anthropometric measures (waist circumference, waist-to-hip ratio).

Main Results:

  • Obesity phenotyping has advanced beyond BMI to include body composition analysis.
  • Phenotypic variability explains differing health risks among individuals with similar BMIs.
  • Refined phenotyping can serve as an early indicator of obesity progression.

Conclusions:

  • A multidimensional approach to obesity assessment is crucial for accurate risk stratification.
  • Nuanced obesity classifications enable personalized therapeutic strategies.
  • Tailored, phenotype-based interventions can optimize weight loss and reduce cardiometabolic risk.