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Related Concept Videos

Introduction to Epidemiology01:26

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
Prevalence and Incidence01:08

Prevalence and Incidence

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin create...
Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...

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Updated: Jun 5, 2026

Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia
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Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia

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Definition, epidemiology, risk factors.

F Galtier1

  • 1HRU Montpellier, Centre d'investigation clinique et Département des Maladies Endocriniennes,, 34295 Montpellier cedex 05, France. f-galtier@chu-montpellier.fr

Diabetes & Metabolism
|December 18, 2010
PubMed
Summary

Gestational diabetes mellitus (GDM) affects 2-6% of pregnancies, rising in diverse populations. Identifying GDM risk factors like prior GDM, age, and obesity is crucial for early detection.

Area of Science:

  • Obstetrics and Gynecology
  • Endocrinology
  • Public Health

Background:

  • Gestational diabetes mellitus (GDM) is glucose intolerance first recognized during pregnancy.
  • Prevalence ranges from 2-6%, escalating to 10-20% in high-risk groups, with increasing trends across various ethnicities.
  • Risk prediction is challenging due to the multiplicity of interacting factors.

Purpose of the Study:

  • To review and synthesize the known risk factors for gestational diabetes mellitus.
  • To highlight the impact of traditional and non-traditional risk factors on GDM development.
  • To discuss the limitations in individual risk prediction for GDM.

Main Methods:

  • Literature review of epidemiological studies on GDM risk factors.
  • Analysis of prevalence data across different populations and ethnic groups.

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  • Categorization of risk factors into traditional (e.g., previous GDM, maternal age, obesity) and non-traditional (e.g., physiological, pathological).

    • Main Results:

    • Previous GDM, advanced maternal age, and obesity are primary risk factors.
    • Racial/ethnic origin and family history of type 2 diabetes have moderate impacts.
    • Non-traditional factors include low birthweight, short maternal height, and polycystic ovary syndrome.

    Conclusions:

    • GDM risk is influenced by a complex interplay of demographic, clinical, and genetic factors.
    • Current understanding of risk factors aids in identifying high-risk pregnancies.
    • The heterogeneity of risk factors limits precise individual risk prediction for GDM.