Dietary Patterns and Hip Fracture Risk in the UK Biobank

Background:

Hip fracture is an increasingly prevalent health problem in the UK and worldwide that increases morbidity and mortality. Previous epidemiological evidence suggests that compared to meat-eaters, people following plant-based diets have lower bone mineral density (BMD) and a higher risk of fractures. Emerging evidence suggests a higher risk of hip fracture in vegetarian women, but prospective evidence of hip fracture risk in these diet groups is scarce and limited, particularly in men. Risk differences between diet groups are plausible in men and women, for example due to bone or muscle-related nutrient deficiencies or low BMI in vegetarians, but underlying mechanisms explaining potential risk differences require further investigation.

This study aims to investigate risk of hip fracture in occasional meat-eaters, pescatarians, and vegetarians compared to regular meat-eaters in the UK Biobank cohort. A secondary aim is to determine the role of potential modifying factors on associations between each diet group and hip fracture risk, including diet quality (determined by adherence to the Alternative Healthy Eating Index, AHEI), age, sex, and BMI, as well as investigating interactions between diet groups and genotypes on BMD and hip fracture risk. Thirdly, we aim to determine the role of potential mediating factors on any observed associations, including BMI, BMD, and intake of dietary nutrients abundant in animal products.

Research plan and methods:

The investigators will utilise dietary and lifestyle data from the UK Biobank cohort, which recruited over 500,000 adults between 2006-2010, and linked hospital records of UK Biobank participants to identify hip fracture cases.

A Cox regression model will be applied to investigate risk of hip fracture in each diet group compared to regular meat-eaters, and will be adjusted for relevant confounders. The roles of age, sex, AHEI score, BMI, and diet-gene interactions as potential effect modifiers will be explored by adding each variable to Cox regression models as interaction terms. Causal mediation analysis will be used to determine the role of potential mediators.

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 hip fracture or osteoporosis 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