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Dietary Factors and Rheumatoid Arthritis Risk in the UK Biobank

Active, not recruiting
Conditions
Rheumatoid Arthritis (RA)
Registration Number
NCT06670183
Lead Sponsor
University of Leeds
Brief Summary

Rheumatoid arthritis (RA) is the most common inflammatory arthritis, affecting around 1% of the UK population. It affects around 400,000 adults and is characterised by synovial inflammation, cartilage and bone damage that requires lifelong treatment and represents a significant burden for both the individual and society. Diet can affect inflammatory status and RA risk, with varying risks for men and women on specific diets. People with low to moderate consumption of alcohol may be at a lower risk of RA. Those who consume lower intakes of fruit and vegetables could be at a greater risk than those with adequate intakes. This research aims to better understand the role of diet in reducing RA risk in men and women in the United Kingdom. The research will use existing dietary and lifestyle data from the United Kingdom Biobank Study and hospital records of RA incidence.

Detailed Description

Background:

RA is the most common inflammatory arthritis in the United Kingdom, contributing significantly to increased morbidity and mortality, particularly from cardiovascular diseases. Epidemiological evidence suggests that compared to occasional drinkers, moderate alcohol consumption may reduce RA risk compared to non-drinkers, and occasional drinking. Additionally, observational research highlights the potential for RA risk reduction through dietary modifications, though evidence on interactions between dietary and genetic factors remains limited, particularly in prospective cohort studies. Moreover, the mechanisms underlying potential differences in RA risk between men and women are not yet fully understood.

This study aims to assess the associations between dietary factors, such as alcohol consumption and dietary patterns, and RA incidence within the UK Biobank cohort. A secondary objective is to evaluate the role of potential modifiers in the relationship between dietary factors and RA risk, including adherence to the Alternative Healthy Eating Index (AHEI), Townsend index, as well as age, sex, body mass index (BMI), smoking status, and physical activity. Additionally, interactions between dietary factors and genetic profiles in relation to RA risk will be investigated.

Research plan and methods:

This study will utilize dietary and lifestyle data from the UK Biobank, a cohort that recruited over 500,000 adults from 2006 to 2010, and linked hospital records to identify incident RA cases.

Cox proportional hazards regression models will be employed to examine associations between dietary factors and RA incidence, adjusting for relevant confounders. Potential effect modifiers such as age, sex, AHEI score, Townsend index, BMI, smoking status, physical activity, and gene-diet interactions will be analyzed by including interaction terms in the Cox models. Causal mediation analysis will further clarify the role of potential mediators. Additionally, inflammatory and immune-related factors, metabolic profile, and genetic susceptibility will be assessed to explore their contributions to RA risk.

Recruitment & Eligibility

Status
ACTIVE_NOT_RECRUITING
Sex
All
Target Recruitment
500000
Inclusion Criteria
  • Male or female
  • Ages 40 to 70 years at time of recruitment
  • Able to provide informed consent
Exclusion Criteria
  • Unable to link dietary and lifestyle data with hospital episode statistics
  • Had a rheumatoid arthritis before or no the date of recruitment
  • Withdrew consent during the study period
  • Genetic sex differs to reported sex
  • Outlier diet or anthropometric data (energy intake <500 or >5000 kcal/day or body mass index <10 or >60 kg/m2)

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Rheumatoid Arthritis incidence (first)Time Frame: Age when the completed questionnaire was returned (2006-2010) until age at event, death, or end of study period (2024).

First RA incidence, identified from all relevant ICD diagnosis codes and treatment codes identified through linked HES data.

Secondary Outcome Measures
NameTimeMethod
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