FROM:
British Medical Journal 2019 (May 14); 365: l1628 ~ FULL TEXT
Hao Ma, PhD candidate, Xiang Li, PhD candidate, Dianjianyi Sun, postdoctoral fellow, Tao Zhou, postdoctoral fellow, Sylvia H Ley, assistant professor, Jeanette Gustat, clinical associate professor, Yoriko Heianza, postdoctoral fellow, Lu Qi, professor
Department of Epidemiology,
School of Public Health and Tropical Medicine,
Tulane University,
New Orleans, LA 70112, USA.
Objective: To prospectively assess the association of habitual glucosamine use with risk of cardiovascular disease (CVD) events.
Design: Prospective cohort study.
Setting: UK Biobank.
Participants: 466,039 participants without CVD at baseline who completed a questionnaire on supplement use, which included glucosamine. These participants were enrolled from 2006 to 2010 and were followed up to 2016.
Main outcome measures: Incident CVD events, including CVD death, coronary heart disease, and stroke.
Results: During a median follow-up of seven years, there were 10,204 incident CVD events, 3,060 CVD deaths, 5,745 coronary heart disease events, and 3,263 stroke events. After adjustment for age, sex, body mass index, race, lifestyle factors, dietary intakes, drug use, and other supplement use, glucosamine use was associated with a significantly lower risk of total CVD events (hazard ratio 0.85, 95% confidence interval 0.80 to 0.90), CVD death (0.78, 0.70 to 0.87), coronary heart disease (0.82, 0.76 to 0.88), and stroke (0.91, 0.83 to 1.00).
Conclusion: Habitual use of glucosamine supplement to relieve osteoarthritis pain might also be related to lower risks of CVD events.
From the Full-Text Article:
Introduction
Glucosamine is a non-vitamin, non-mineral supplement widely used to relieve osteoarthritis and joint pain. [1] Glucosamine is closely regulated in most European countries, where it is only sold with a prescription. However, in other countries such as the United States and Australia, it is a popular dietary supplement and approximately 20% of adults consume it daily. [2, 3]
The effectiveness of glucosamine in patients with osteoarthritis and joint pain continues to be debated. [4, 5] Emerging evidence from epidemiological studies suggests that glucosamine could have a role in preventing cardiovascular disease (CVD)3 and reducing mortality. [6] A previous animal study reported that glucosamine extended life span by mimicking a low carbohydrate diet, [7] and studies in humans have consistently shown the protective effect of a low carbohydrate diet on the development of CVD. [8–16] Other animal studies have reported that the anti-inflammatory properties of glucosamine might have a preventive role in atherosclerosis development. [17–21]
In this prospective cohort study, we examined the association between habitual glucosamine supplement use and risk of CVD events (CVD death, coronary heart disease (CHD), and stroke) in nearly half a million adults in the UK Biobank. We also analyzed potential effect modification by other known risk factors for CVD.
Methods
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. [22, 23] 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=4,390). 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. [24, 25] 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. [29, 30] We calculated the genetic risk scores for CHD and stroke based on previously reported genetic variants [31, 32]: 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.
Results
Table 1
Table 2
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Table 1 shows baseline characteristics of the study participants according to the use of glucosamine. Overall, 19.3% of the study population reported glucosamine use at baseline. Compared with non-users, glucosamine users were older, more likely to be women, not current smokers, more physically active, had a healthy diet, had a lower alcohol intake, and had a higher prevalence of hypertension, arthritis, and high cholesterol, but a lower prevalence of diabetes. Glucosamine users also tended to take more aspirin, non-aspirin non-steroidal anti-inflammatory drugs, vitamins, minerals, and other dietary supplements than non-users.
Table 2 shows the associations between glucosamine use and incident CVD events. During a median follow-up of seven years, we recorded 10,204 incident CVD events, 3,060 CVD deaths, 5,745 incident CHD events, and 3,263 incident stroke events. In the age adjusted analyses, we found significant inverse associations between glucosamine use and risk of total CVD events, CVD death, CHD, and stroke (all P<0.001). In the multivariable adjusted analyses, the hazard ratios associated with glucosamine use were 0.85 (95% confidence interval 0.80 to 0.90; P<0.001) for total CVD events; 0.78 (0.70 to 0.87; P<0.001) for CVD death; 0.82 (0.76 to 0.88; P<0.001) for CHD; and 0.91 (0.83 to 1.00; P=0.04) for stroke.
We analyzed the relations between glucosamine use and subtypes of CHD and stroke. For CHD, glucosamine use was associated with significantly lower risks of non-fatal CHD (hazard ratio 0.84, 95% confidence interval 0.77 to 0.91; P<0.001) and fatal CHD (0.70, 0.59 to 0.85; P<0.001). For stroke, glucosamine use was associated with a marginally significantly lower risk of non-fatal stroke (0.91, 0.82 to 1.01; P=0.08), but it was not associated with risk of fatal stroke (0.87, 0.68 to 1.13; P=0.30). There was no significant inverse association between glucosamine use and risk of ischemic stroke (0.92, 0.80 to 1.03; P=0.14) or hemorrhagic stroke (0.89, 0.75 to 1.07; P=0.21).
Figure 1
Figure 2
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We conducted stratified analyses according to potential CVD risk factors. We observed consistent and significant interactions between glucosamine use and smoking on risks of CVD events and CHD (P for interaction=0.02 and 0.004, respectively) (Figures 1 and 2). The associations between glucosamine use and these CVD outcomes were stronger among current smokers than among former or never smokers. The associations between glucosamine use and CVD outcomes were not modified by other risk factors, including age, sex, body mass index, physical activity, healthy diet, diabetes, hypertension, high cholesterol, arthritis, and aspirin and non-aspirin non-steroidal anti-inflammatory drug use (figs 1 and 2).
did not change appreciably: first, when we excluded participants who used any other supplements (supplementary table 3); second, when we excluded participants who developed CVD events within two years of follow-up (supplementary table 4); and third, after additional adjustment for genetic predisposition to CHD or stroke (CHD or stroke genetic risk score; supplementary table 5). In addition, we did not find significant interactions between glucosamine use and CHD genetic risk score on the risk of CHD (P for interaction=0.35) or significant interaction between glucosamine use and stroke genetic risk score on the risk of stroke (P for interaction=0.35).
Discussion
In this large prospective study, habitual glucosamine use was associated with a 15% lower risk of total CVD events and a 9%–22% lower risk of individual cardiovascular events (CVD death, CHD, and stroke). Such associations were independent of traditional risk factors, including sex, age, income, body mass index, physical activity, healthy diet, alcohol intake, smoking status, diabetes, hypertension, high cholesterol, arthritis, drug use, and other supplement use. In addition, we found that the associations between glucosamine use and CVD outcomes were statistically significantly modified by smoking status.
Comparison with other studies
Our findings are in line with several previous studies that show inverse associations of glucosamine use with CVD risk and mortality. In a cross sectional study of 266,844 Australian participants, glucosamine use was found to be inversely associated with risks of heart attack or angina (odds ratio 0.79, 95% confidence interval 0.73 to 0.86) and other heart diseases (0.82, 0.76 to 0.89). [3] In the Vitamins and Lifestyle (VITAL) cohort study, glucosamine use was significantly associated with an 18% lower risk of total mortality. [6, 34] Similarly in our study, we found that glucosamine use was consistently associated with lower risks of subtypes of CHD, including fatal and non-fatal CHD. Our lack of statistically significant associations between glucosamine use and subtypes of stroke is probably because of small numbers of participants in the subtype groups.
Biological plausibility
Several potential mechanisms could explain the observed protective relation between glucosamine use and CVD diseases. In the National Health and Nutrition Examination Survey (NHANES) study, regular use of glucosamine was associated with a statistically significant reduction in C reactive protein concentrations, which is a marker for systemic inflammation. [35] Animal studies also reported that the anti-inflammatory properties of glucosamine might have a preventive role in the pathophysiology of CVD. [17–21] In addition, a previous study found that glucosamine could mimic a low carbohydrate diet by decreasing glycolysis and increasing amino acid catabolism in mice [7]; therefore, glucosamine has been treated as an energy restriction mimetic agent.36 Low carbohydrate diets have been related to a reduced risk of CVD in epidemiological studies, [8, 9] and several recent diet intervention trials report that a low carbohydrate diet has a protective effect against the development of CVD. [10–16] Other mechanisms might also be involved, and future investigations are needed to explore the functional roles of glucosamine in cardiovascular health.
We found consistent interactions between glucosamine use and smoking on CVD outcomes. Inverse associations of glucosamine use with CVD outcomes were stronger in current smokers than in former smokers or never smokers. We found habitual glucosamine use was associated with a 12% and an 18% lower risk of CHD in never and former smokers, respectively, compared with a 37% lower risk in current smokers. We could not rule out the possibility that these results were due to chance. However, smokers have higher levels of inflammation and a higher risk of CVD compared with non-smokers. [37] Additionally it has been hypothesized that anti-inflammatory agents might be more effective in participants with higher inflammation stress [37, 38]; thus the interaction between glucosamine use and smoking is biologically feasible. Given the important role smoking has in the development of CVD, further studies are needed to evaluate the effect of glucosamine in CVD prevention, particularly among current smokers.
Strengths and limitations of this study
Our study has several major strengths, including the large sample size and the wealth of information on lifestyle, diet, and other covariates, which enabled us to conduct comprehensive sensitivity analyses and subgroup analyses. We acknowledge that our study also has potential limitations. First, the UK Biobank did not record detailed information on glucosamine use, such as the dosage and the duration of use. Therefore, further studies are needed to investigate such associations. Second, the UK Biobank did not collect information on the side effects of glucosamine use. However, glucosamine has been rated the safest supplement for osteoarthritis, with few side effects reported, such as occasional allergic reactions, diarrhea, constipation, nausea, and heartburn.1 Although previous studies have suggested that glucosamine might worsen glucose tolerance in participants with a high risk of diabetes, [39, 40] clinical trials have shown that glucosamine has no effect on glucose metabolism and lipid profile at any oral dose in healthy participants and patients with diabetes. [41–43]
A third limitation is that specific information on forms of glucosamine supplement (glucosamine sulfate, glucosamine hydrochloride, N acetyl glucosamine) was not collected, and so it was difficult to assess whether the association between various forms of glucosamine supplement and CVD risk might differ. However, most glucosamine products available on the market contain glucosamine sulfate. Fourth, it is difficult to separate the effects of a healthy lifestyle from the use of habitual supplements in an observational study. Habitual glucosamine use might be a marker for a healthy lifestyle in this study. Therefore, we could not exclude the possibility that the observed inverse associations were driven by healthy lifestyle factors among glucosamine users, although we had carefully adjusted for potential confounding in our analyses. Finally, potential reverse causality might still exist in our study, although the results remained unchanged when we excluded participants with CVD events that occurred during the first two years of follow-up.
Conclusions
Habitual use of glucosamine supplement to relieve osteoarthritis pain might also be related to lower risks of CVD events. Further clinical trials are needed to test this hypothesis.
What is already known on this topic
Glucosamine supplement is commonly used to treat osteoarthritis, but its effectiveness in relieving osteoarthritis and joint pain continues to be debated
Recent evidence from animal studies and cross sectional studies in humans suggests that glucosamine could have a role in preventing cardiovascular disease (CVD) and reducing mortality; however, evidence from prospective studies is lacking
What this study adds
Habitual glucosamine use was associated with a 15% lower risk of total CVD events and a 9%–22% lower risk of individual CVD events (CVD death, coronary heart disease, and stroke)
These findings suggest that glucosamine might have a preventive role in the development of CVD, but further clinical trials are needed to test this hypothesis
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Additional files
Additional Tables 1–5
(283K, pdf)
Contributors:
LQ and HM conceived and designed the study. HM performed the statistical analysis. HM and LQ wrote the first draft of the manuscript. All the authors participated in the interpretation of the results and critical revision of the manuscript. LQ had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; he is the guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.
Funding:
LQ was supported by grants from the National Heart, Lung, and Blood Institute (HL071981, HL034594, HL126024) and the National Institute of Diabetes and Digestive and Kidney Diseases (DK115679, DK091718, DK100383, DK078616). SHL is partially supported by grant P20GM109036 from the National Institute of General Medical Sciences of the National Institutes of Health.
Competing interests:
All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
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