Related Experiment Video

Updated: Jun 8, 2025

Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes
07:22

Glycemic Impact on Knee Osteoarthritis Symptoms on Physical, Radiographic, and Inflammatory Markers among Individuals Aged 50 and Over with Diabetes

Published on: March 7, 2025

200

Investigating the correlation of hip circumference to cardiovascular disease and type-2 diabetes using Mendelian

Hongtao Liu1, Zhaoyu Li2, Su Yan2

  • 1Guangxi Health Science College, Nanning, China.

Journal of Diabetes Investigation
|November 7, 2024
PubMed

Insights

Hip circumference (HC) is causally linked to cardiovascular disease (CVD) and type 2 diabetes mellitus risk. After adjusting for body mass index (BMI), increased hip fat offers protection against type 2 diabetes mellitus but not CVD.

Area of Science:

  • Genetics
  • Metabolic Diseases
  • Cardiovascular Health

Background:

  • Observational studies suggest associations between hip circumference (HC) and cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM).
  • Mendelian randomization (MR) can overcome limitations of observational studies by using genetic variants as instrumental variables.

Purpose of the Study:

  • To assess the causal relationship between hip circumference (HC) and the risk of cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM).
  • To investigate whether these relationships are independent of body mass index (BMI).

Main Methods:

  • Two-sample Mendelian randomization (MR) analysis using genetic variation data from MR Base.
  • Employed MR-Egger regression, weighted median estimator, and inverse variance weighting (IVW) methods.
  • Utilized summary statistics from genome-wide association studies (GWAS) for HC (adjusted and unadjusted for BMI) as exposures and CVD and T2DM as outcomes.

Main Results:

  • Unadjusted HC showed a positive causal association with both CVD and T2DM.
  • After adjusting for BMI, HC was not significantly associated with CVD.
  • BMI-adjusted HC exhibited a negative causal association with T2DM, suggesting a protective effect.

Conclusions:

  • Adipose tissue distribution, specifically hip circumference, plays a differential role in metabolic and cardiovascular health.
  • Increased hip fat, after accounting for overall adiposity (BMI), appears protective against type 2 diabetes mellitus.
  • Findings suggest potential implications for T2DM prevention and treatment strategies, and warrant further investigation into underlying mechanisms.
Abstract

Keywords:
Hip circumferenceMendelian randomizationType 2 diabetes mellitus

More Related Videos

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model06:22

Modeling and Evaluation of Murine Diabetic Cardiomyopathy Model

Published on: November 29, 2024

532
Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome06:04

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome

Published on: September 27, 2024

806

Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.5K
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
161
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
145
Cholesterol: Significance and Regulation01:29

Cholesterol: Significance and Regulation

Although not a source of energy, cholesterol plays a significant role as a foundational structure for bile salts, steroid hormones, and vitamin D, as well as being a crucial component of plasma membranes. Approximately 15% of blood cholesterol is derived from our diet, with the remainder synthesized from acetyl CoA by the liver and intestines. Cholesterol is eliminated from the body through its conversion into bile salts, which are eventually discarded in the feces.
Considering cholesterol and...
511
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
91