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Obesity: History, Community, Culture & Applications

Obesity is a medical condition, considered a disease by multiple organizations, in which excess body fat has accumulated to such an extent that it can have negative effects on health. People are classified as obese when their body mass index (BMI)—a person's weight divided by the square of the person's height—is over 30 kg/m2; the range 25–30 kg/m2 is…

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Obesity topic overview

The analysis highlights History, Community, Culture and Applications as prominent areas in the source structure around Obesity.

Related topics
268
Source areas
11
Connected nodes
281
Extracted relationships
359
Concept neighborhoods
60
Bridge connections
281

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Causes · 83 topics
Overview · 46 topics
Society and culture · 29 topics
Effects on health · 21 topics
Medical interventions · 20 topics
History · 19 topics
Pathophysiology · 14 topics
Management · 13 topics
Classification · 12 topics
Childhood obesity · 6 topics
Epidemiology · 5 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Causes
Excessive consumption of energy-dense foods, sedentary work and lifestyles and lack of physical activity, changes in modes of transportation, urbanization, lack of supportive po…
Complications
Cardiovascular diseases, type 2 diabetes, obstructive sleep apnea, certain types of cancer, osteoarthritis, depression
Deaths
2.8 million people per year
Diagnostic method
BMI > 30 kg/m2
Frequency
Over 1 billion / 12.5% (2022)
Prevention
Societal changes, changes in the food industry, access to a healthy lifestyle, personal choices

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Classification

Effects on health

Causes

Pathophysiology

Management

Medical interventions

Epidemiology

History

Society and culture

Childhood obesity

Sources

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How Obesity connects Entity context

The extracted context around Obesity shows recurring relationship patterns in the source. For example, Obesity → Adults, Canadian Clinical Practice Guidelines, Canadian Obesity Network, Care Research, Child Health, Children, Clinical Excellence, Clinical Guidelines, Commons Health Select Committee, CPG, Derek Wanless, Evaluation, Faculty, Health, House, Identification, In, King's Fund, Management, Many Another extracted example is Obesity → After, Alessandro, Blackburn, Borro, Christian European, Corpulence, During, England, Female Reformers, George Cruikshank, Greek, Henry VIII, In, Renaissance, Roman, Rubenesque, Rubens, Some, The, The Belle Alliance. Use these groups to spot repeated connection types before inspecting the individual relationships.

Obesity

Top relations

related to Reports · 40
Obesity → Adults, Canadian Clinical Practice Guidelines, Canadian Obesity Network, Care Research, Child Health, Children, Clinical Excellence, Clinical Guidelines, Commons Health Select Committee, CPG, Derek Wanless, Evaluation, Faculty, Health, House, Identification, In, King's Fund, Management, Many
related to The arts · 24
Obesity → After, Alessandro, Blackburn, Borro, Christian European, Corpulence, During, England, Female Reformers, George Cruikshank, Greek, Henry VIII, In, Renaissance, Roman, Rubenesque, Rubens, Some, The, The Belle Alliance
related to Diet · 20
Obesity → America, Asia, Consumption, Dietary, During, Eastern Europe, Europeans, Excess, For, From, It, Most, Saharan Africa, The, The United States, This, Total, United States, Vitamin, Western
related to Historical attitudes · 19
Obesity → Ancient East Asian, Ancient Egyptians, Ancient Greek, BCE, Corpulence, During, English, For, He, Height, Hippocrates, In, Increasing, Industrial Revolution, It, Sushruta, The Indian, Tobias Venner, With
related to Genetics · 16
Obesity → Advances, Bardet, Biedl, BMI, Cohen, DNA, FTO, GWAS, In, Like, MOMO, People, Polymorphisms, Prader, The, Willi
related to Childhood obesity · 14
Obesity → Advertising, Antibiotics, As, Because, BMI, Brazilian, Canadian, Changing, Childhood, In, Rates, The, UK, US
related to Survival paradox · 12
Obesity → Although, Another, BMI, COPD, Even, In, One, PAD, People, Similar, The, This
related to Epidemiology · 11
Obesity → As, BMI, But, Early Modern, In, Prior, The, Then, United States, WHO, World Health Organization
related to Sedentary lifestyle · 11
Obesity → Atlanta-area, BMI, Community, Finland, In, Physical, The World Health Organization, This, United States, World, Worldwide
related to Classification · 10
Obesity → BMI, CDC, Centers, Disease Control, For, Medical, Prevention, The, WHO, World Health Organization

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

weight obese people health bmi food fat risk body children overweight increased physical diet world also rates disease energy found

Obesity relationships Subject–Predicate–Object triples

TTTA extracted 359 structured relationships around Obesity. Examples in this analysis include Obesity → Causes → Excessive consumption of energy-dense foods, sedentary work and lifestyles and lack of physical activity, changes in modes of transportation, urbanization, lack of supportive po… and Obesity → Complications → Cardiovascular diseases, type 2 diabetes, obstructive sleep apnea, certain types of cancer, osteoarthritis, depression. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
ObesityCausesExcessive consumption of energy-dense foods, sedentary work and lifestyles and lack of physical activity, changes in modes of transportation, urbanization, lack of supportive po…1.00infobox
ObesityComplicationsCardiovascular diseases, type 2 diabetes, obstructive sleep apnea, certain types of cancer, osteoarthritis, depression1.00infobox
ObesityDeaths2.8 million people per year1.00infobox
ObesityDiagnostic methodBMI > 30 kg/m21.00infobox
ObesityFrequencyOver 1 billion / 12.5% (2022)1.00infobox
ObesityPreventionSocietal changes, changes in the food industry, access to a healthy lifestyle, personal choices1.00infobox
ObesityPrognosisReduced life expectancy1.00infobox
ObesitySpecialtyEndocrinology, bariatrics, family medicine1.00infobox
ObesitySymptomsIncreased fat1.00infobox
ObesityTreatmentDiet, exercise, medications, surgery1.00infobox
Obesityis amedical condition0.90text
Obesityis amajor cause of disability and is correlated with various diseases and conditions0.90text
Obesityis aleading preventable cause of death worldwide0.90text
Obesityis asingle strongest risk factor for severe COVID-19 illness.Complications may be either directly caused by obesity or indirectly related through mechanisms sharing a common cause s…0.90text
Obesityis adisorder of the energy homeostasis system0.90text
Obesityis aresult of an interplay between genetic and environmental factors0.90text
Obesityis amajor feature in several syndromes0.90text
Obesityis amain feature0.90text
Obesityis adisability0.90text

Related concept clusters Concept neighborhoods

The concept neighborhoods around Obesity bring nearby vocabulary together. In this analysis, examples include Rates, Risk and People. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Obesity
    • Rates
    • Risk
    • People
    • Weight
    • Children
    • World
    • Increased
    • Also
    • Increasing
    • Adults
    • Among
    • However
  • obesity
    • Rates
    • Risk
    • People
    • Weight
    • Children
    • World
    • Increased
    • Also
    • Increasing
    • Adults
    • Among
    • However
  • disease
    • Medical
    • Diabetes
    • Health
    • World
    • Risk
    • Effects
    • Obese
    • Found
    • Obesity
    • Fat
    • Body
    • Increased
  • body fat
    • Fat
    • Weight
    • Bmi
    • Food
    • Diet
    • Increased
    • Changes
    • People
    • Diabetes
    • Energy
    • Effects
    • Cause
  • health
    • World
    • Obesity
    • Research
    • Kg
    • Bmi
    • Medical
    • However
    • Increased
    • Obese
    • United
    • Overweight
    • Physical
  • body mass index
    • Fat
    • Weight
    • Bmi
    • Increased
    • People
    • Energy
    • Cause
    • Effects
    • Medical
    • Changes
    • Increasing
    • Obese
  • world health organization
    • Health
    • World
    • Obesity
    • Research
    • Kg
    • Rates
    • Bmi
    • United
    • Medical
    • However
    • Adults
    • Disease
  • american medical association
    • Disease
    • Research
    • People
    • Health
    • Diabetes
    • Body
    • Effects
    • Obesity
    • Fat
    • Obese
    • Bmi
    • Kg

Connections between topic areas Semantic bridges

For Obesity, one of the stronger structural bridges in this analysis connects Obesity with Causes. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3
ObesityCauses · splits 198 ⟂ 84
ObesityOverview · splits 235 ⟂ 47
ObesitySociety and culture · splits 252 ⟂ 30
ObesityEffects on health · splits 260 ⟂ 22
ObesityMedical interventions · splits 261 ⟂ 21
ObesityHistory · splits 262 ⟂ 20
ObesityPathophysiology · splits 267 ⟂ 15
ObesityManagement · splits 268 ⟂ 14
ObesityClassification · splits 269 ⟂ 13
ObesityChildhood obesity · splits 275 ⟂ 7
ObesityEpidemiology · splits 276 ⟂ 6

Map overview Semantic statistics

Obesity

Nodes282
Edges281
Triples359
Avg. degree1.99
Density0.007092
Components1

Source & methodology

TTTA analyzes the structure around Obesity to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Community, Culture & Applications, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Obesity · EN edition · Analysis: TopicsToTalkAbout

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