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Study population

The UK Biobank is a national health resource in the United Kingdom designed to improve the prevention, diagnosis, and treatment of a wide range of illnesses and to promote health throughout society.2223 The UK Biobank recruited around 500 000 participants aged 40-69 in 2006-10 from across the country. 

Data from 502 616 participants were available for our study. We excluded participants with CVD at baseline (n=32 187) and those with incomplete data on the use of glucosamine (n=4390). Our final analysis included 466 039 participants.

Exposure assessment

Participants attended one of 22 assessment centers across the UK where they completed a touch screen questionnaire. One of the questions asked “Do you regularly take any of the following?”, and participants could select their answer from a list of supplements, which included glucosamine. From this information, we defined glucosamine use as 0=no and 1=yes.

We used the baseline touch screen questionnaire to assess several potential confounders: age, sex, race, household income, smoking status, and alcohol intake (we calculated ethanol intake by multiplying the quantity of each type of drink—red wine, white wine, beer or cider, fortified wine, or spirits—by its standard drink size and reference alcohol content); self reported diabetes and high cholesterol level; drugs to treat high cholesterol, high blood pressure, and diabetes; aspirin and other non-steroidal anti-inflammatory drug use; and dietary intakes (red meat, vegetables, fruit, fish, and cereals).

We calculated the healthy diet score by using the following factors: red meat intake up to three times each week (median); vegetable intake at least four tablespoons each day (median); fruit intake at least three pieces each day (median); fish intake at least four times each week (median); cereal intake at least five bowls each week (median); and urinary sodium concentration up to 70.6 mmol/L (median). We gave 1 point for each favorable diet factor, and the total diet score ranged from 0 to 6.2425 A healthy diet was defined as a diet score of 3 or more.26

The ion selective electrode method (AU5400 analyzer, Beckman Coulter) was used to measure sodium levels in stored urine samples. The analytic range for sodium was 2-200 mmol/L. Details on quality control and sample preparation have been published previously.27 Body mass index was calculated by dividing a participant’s weight, measured to the nearest 0.1 kg using the Tanita BC-418 MA body composition analyzer (Tanita Corporation of America, IL), by the square of his or her standing height in meters, measured with a Seca 202 device (SECA, Hamburg, Germany). 

According to global recommendations on physical activity for health,28 we categorized participants into two groups based on total moderate physical activity minutes each week (one vigorous physical activity minute equals two moderate physical activity minutes): <150 or ≥150 min/week. Hypertension was defined as a self reported history of hypertension, systolic blood pressure of 140 mm Hg or higher, diastolic blood pressure of 90 mm Hg or higher, or taking antihypertensive drugs. Arthritis was defined by ICD-10 (international classification of diseases, 10th revision) codes M15-M19.

Genotyping and genetic risk scores

Detailed information about genotyping and imputation in the UK Biobank has been previously published.2930 We calculated the genetic risk scores for CHD and stroke based on previously reported genetic variants3132: 63 single nucleotide polymorphisms (SNPs) were used for CHD, and 27 SNPs were used for stroke (supplementary tables 1 and 2). In our analytic sample, we had data for 393 771 participants to calculate CHD genetic risk score, and data for 330 419 participants to calculate stroke genetic risk score by using a weighted method.33 Each SNP was recoded as 0, 1, or 2 according to the number of risk alleles. Each SNP was multiplied by a weighted risk estimate (natural logarithm of the odds ratio) for CHD or stroke obtained from the previous genome wide association study. We then added up these products. The CHD genetic risk score ranged from 3.06 to 6.54 and the stroke genetic risk score ranged from 0.52 to 3.43. Higher scores indicate a higher genetic predisposition to CHD or stroke.

Ascertainment of outcomes

The primary outcomes for this study were CVD events: CVD death, CHD, and stroke. Secondary outcomes were individual CHD events (fatal and non-fatal) and individual stroke events (fatal and non-fatal; ischemic and hemorrhagic stroke). Information on CVD events and timing of events was collected through certified death records (until 16 February 2016) and cumulative medical records of hospital diagnoses. Additional information was collected through two repeated surveys (the first visit was completed between 12 December 2009 and 7 June 2013; the second visit between 30 April 2014 and 10 August 2017).

ICD-10 codes were used in death records, whereas ICD-10 and ICD-9 (international classification of diseases, ninth revision) codes were used in medical records. CHD was defined as ICD-9 codes 410-414 and ICD-10 codes I20-I25. Stroke was defined as ICD-9 codes 430-434 and 436, and ICD-10 codes I60-I64 (ischemic stroke: ICD-9 codes 433-434, ICD-10 code I63; hemorrhagic stroke: ICD-9 codes 430-432, ICD-10 codes I60-I62). CVD death was defined as ICD-10 codes I00-I99.

Statistical analysis

We compared event rates in participants who did and did not use glucosamine by using Cox proportional hazards models to calculate hazard ratios and 95% confidence intervals. The proportional hazards assumption was tested using Schoenfeld residuals. We adjusted for several potential confounders: age, sex, and race (white European, mixed, South Asian, black, others); average total annual household income (<£18 000 ($23 500; €21 000), £18 000-£30 999, £31 000-£51 999, £52 000-£100 000, >£100 000, and “do not know” or missing); body mass index; smoking status (current, former, never, missing); alcohol intake (g/week); physical activity (<150 or ≥150 min/week); diabetes (yes, no, or missing), hypertension (yes or no), high cholesterol (yes or no), and arthritis (yes or no); antihypertensive drugs (yes or no), lipid treatment (yes or no), insulin treatment (yes or no), aspirin use (yes or no), and non-aspirin non-steroidal anti-inflammatory drug use (yes or no); healthy diet (yes or no); vitamin supplement use (yes or no; multivitamin, folic acid, vitamin A, vitamin B, vitamin C, vitamin D, vitamin E); and mineral and other dietary supplement use (yes or no; calcium, iron, zinc, selenium, fish oil). We coded missing data as a missing indicator category for categorical variables such as smoking status, and with mean values for continuous variables.

We conducted a stratified analysis to assess potential modification effects by the following factors: sex (women or men), age (<55 or ≥55), body mass index (18.5-24.9, 25.0-29.9, or ≥30), physical activity (<150 or ≥150 min/week), smoking (never, former, or current), healthy diet (yes or no), diabetes (yes or no), hypertension (yes or no), high cholesterol (yes or no), arthritis (yes or no), aspirin use (yes or no), and non-aspirin non-steroidal anti-inflammatory drug use (yes or no). We evaluated potential effect modification by modeling the cross product term of the stratifying variable with glucosamine use.

We conducted several sensitivity analyses. First, because participants who took glucosamine also tended to take other supplements more often than participants who did not take glucosamine, we did a sensitivity analysis by excluding participants who used any other supplements. Second, to minimize the influence of reverse causation, we performed a sensitivity analysis by excluding participants who developed CVD events within two years of follow-up. Third, to control the influence of genetic predisposition to CHD or stroke, we adjusted for CHD or stroke genetic risk score.

We conducted all statistical analyses by using SAS version 9.4 (SAS Institute, Cary, NC). All statistical tests were two sided, and we considered a P value less than 0.05 to be statistically significant.

Patient and public involvement

No patients were involved in setting the research question or the outcome measures, nor were they involved in the design and implementation of the study. No plans exist to disseminate the results to study participants.