Chronic Inflammatory Disease, Lifestyle and Risk of Disease

Summary

Participation Requirements

Description

Material and methods: The study design is a cohort study with prospective register data follow up. The Danish cohort "Diet, Health and Cancer" (DHC) will be used. The DHC Study is an ongoing Danish cohort study designed to investigate the relation between diet, lifestyle and disease risk. The cohort...

Material and methods: The study design is a cohort study with prospective register data follow up. The Danish cohort "Diet, Health and Cancer" (DHC) will be used. The DHC Study is an ongoing Danish cohort study designed to investigate the relation between diet, lifestyle and disease risk. The cohort consists of 57,053 persons, recruited between December 1993 and May 1997. All the subjects (50 to 64 years of age) gave detailed information on diet (food frequency questionnaire) and other lifestyle data together with biological samples. Blood samples, anthropometric measures and questionnaire data on diet and lifestyle were collected at study entry. Data from the DHC cohort will be combined with Danish national registers (the National Patient Registry (NPR), the Danish Civil Registration Register, and The Danish National Prescription Registry). Outcome measures and follow-up: The National Patient Registry (NPR) will be used to obtain to identify patients with CID during follow-up. The NPR contains data on all patients admitted to Danish hospitals since 1977. The register covers both inpatient and outpatient records and indicates the main medical reason for diagnostic procedures or treatment (since 1994 according to the tenth version of the International Classification of Diseases (ICD-10)). For this study there will be extracted data from NPR from 1993 to March 2018. The outcome CID is defined as at least one of the following diseases in the NPR; inflammatory bowel disease (IBD) (ICD10 codes: K50-K51), psoriasis/psoriatic arthritis (ICD10 codes: M073, M090, L40), rheumatoid arthritis/ankylosing arthritis (ICD10 codes: M059. M060, M069, M089, M459, M46), or multiple sclerosis (ICD10 codes: G35, G35.9), during the follow-up period. The Danish National Prescription Registry will be used to identify the most severe cases of the following diseases listed above, as it is expected that the patients have medication in relation to the diseases. Follow-up information on death and immigration will be collected in March 2018 from the Danish Civil Registration Register. Exposure and possible confounders: Information on exposure is defined as high fibre intake and high red and processed meat intake and were collected at enrolment of the DHC cohort using questionnaires and interviews. In short, the food-frequency questionnaire, diet consumption was assessed in 12 categories of predefined responses, ranking from "never" to "eight times or more per day". The daily intake was then calculated by the software program FoodCalc. FoodCalc is a simple program to calculate intake of nutrients when given a list with amounts of different foods consumed and another list with contents of nutrients for the different foods. Both intake of dietary fibre and red meat and processed meat were measured as continues variable in g/day. Information on possible confounders will also be obtained from the questionnaire data at enrolment in relation to sex, age, BMI, smoking and other lifestyle factors and information on co-morbidity will be obtained from NPR. Statistical analyses: The intention is to use data obtained from this prospective cohort study to explore the ability to predict risk of CID (Y=primary endpoint) and to explore whether diets low in fibre AND high in red and processed meat (X=assessed at baseline) are an informative prognostic factor on disease risk. Descriptive analyses for categorical variables will be presented as frequencies, and differences between CID cases and non-cases will be evaluated by Chi-square test. Continuous variables will be tabulated as medians (with quartiles, Q1 and Q3) and nonparametric tests on the equality of medians will be used to test for differences between groups. P-values below 0.05 will be considered statistically significant. Negative binomial regression will be applied to calculate incidence rates per 1000 patient years and incidence rate ratios (IRR) between exposures. To investigate the risk of and time to CID-diagnosis the Fine-Gray competing risk regression model will be applied, and thus competing risk of death will be taken into account while handling emigration as censoring, and reporting cumulative incidences and sub-hazard ratios (SHR) and the corresponding p-values for CID associated with specified food substitutions. Regressions will be carried out as both crude regression, only including the exposure, and adjusted for age, sex, lifestyle factors and selected comorbidities. Analyses will be conducted using Stata. To test if the hypothesized causality between diet factors and development of CID is applicable for all of the CIDs there will be conducted subanalyses on each of the CID-diagnoses. Sensitivity analyses will be conducted on data from the Danish National Prescription Registry to evaluate the validity of the CID diagnoses, as it is expected that they get treatment in relation to the diseases. Data on medication and treatment of each diagnosis will be analysed separately.

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