Abstract

The association of antioxidant vitamins and trace elements from foods and supplements with risk of rheumatoid arthritis was evaluated in a prospective cohort study of 29,368 women who were aged 55–69 years at baseline in 1986. Through 1997, 152 cases of rheumatoid arthritis were identified. After controlling for other risk factors, greater intakes (highest tertile vs. lowest) of supplemental vitamin C (relative risk (RR) = 0.70, 95% confidence interval (CI): 0.48, 1.09; p-trend = 0.08) and supplemental vitamin E (RR = 0.72, 95% CI: 0.47, 1.12; p-trend = 0.06) were inversely associated with rheumatoid arthritis. There was no association with total carotenoids, α- or β-carotene, lycopene, or lutein/zeaxanthin, while there was an inverse association with β-cryptoxanthin (RR = 0.59, 95% CI: 0.39, 0.90; p-trend = 0.01). Greater use of supplemental zinc (RR = 0.39, 95% CI: 0.17, 0.88; p-trend = 0.03) was inversely associated with rheumatoid arthritis, while any use of supplemental copper (RR = 0.54, 95% CI: 0.28, 1.03) and manganese (RR = 0.50, 95% CI: 0.23, 1.07) showed suggestive inverse associations with rheumatoid arthritis. Greater intakes of fruit (RR = 0.72, 95% CI: 0.46, 1.12; p-trend = 0.13) and cruciferous vegetables (RR = 0.65, 95% CI: 0.42, 1.01; p-trend = 0.07) also exhibited trends toward inverse associations with risk. When the antioxidants were modeled together, only β-cryptoxanthin and supplemental zinc were statistically significant predictors. Intake of certain antioxidant micronutrients, particularly β-cryptoxanthin and supplemental zinc, and possibly diets high in fruits and cruciferous vegetables, may be protective against the development of rheumatoid arthritis.

Received for publication February 20, 2002; accepted for publication September 3, 2002.

Rheumatoid arthritis is a chronic inflammatory disease of unknown etiology that affects approximately 1 percent of the adult population worldwide (1, 2). A hallmark of the disease is a persistent inflammation of the synovium of the joints, leading to destruction of the surrounding bone and cartilage and ultimately joint deformities. Free oxygen radicals (e.g., superoxide and hydrogen peroxide) have been implicated as mediators of tissue damage in rheumatoid arthritis, along with proinflammatory cytokines, particularly tumor necrosis factor-α (3–5). Free radical oxidation products have been identified in the synovial fluid of rheumatoid arthritis patients (6, 7), and these products are thought to be generated by activated macrophages, monocytes, and granulocytes (3, 4), as well as by anoxic reperfusion reactions that may occur with the movement of affected joints (8). Antioxidant micronutrients play an important role as part of the mechanism that protects against tissue damage caused by reactive oxygen species (3). Antioxidants also suppress the expression of cytokines and collagenase induced by tumor necrosis factor-α (9), which suggests additional mechanisms of protection against rheumatoid arthritis.

These observations have led to the hypothesis that antioxidant compounds may protect against the development or progression of rheumatoid arthritis. While use of antioxidants (or other dietary manipulations) in the treatment of rheumatoid arthritis has a controversial history, there are few data on the role of these agents in the etiology of rheumatoid arthritis (10–12). Patients with rheumatoid arthritis have been reported to have lower serum levels of a variety of antioxidants, including vitamin E, vitamin C, β-carotene, selenium, and zinc, in comparison with controls, but these associations may be a result of the disease or its treatment (4, 12). In two nested case-control studies using serum obtained prior to diagnosis of rheumatoid arthritis, selenium, α-tocopherol, β-carotene, and an overall antioxidant index were inversely associated with the later development of rheumatoid arthritis (13, 14). In a case-control study assessing dietary intake using a food frequency questionnaire, intake of vitamin C, but not intake of vitamin E, was weakly and inversely associated with rheumatoid arthritis (15). Diets high in fruits or vegetables have also been suggested to be protective against rheumatoid arthritis (15, 16).

Evaluation of dietary hypotheses in the etiology of rheumatoid arthritis is greatly complicated by the fact that the clinical course and treatment of the disease has multiple nutritional consequences, including altered appetite and altered nutrient absorption, metabolism, and excretion (17). In addition, many rheumatoid arthritis patients believe that diet influences their disease, and a large percentage may attempt dietary therapies with or without physician supervision (17). These changes are a major source of potential bias in case-control studies evaluating diet in the etiology of rheumatoid arthritis. In contrast, prospective cohort studies avoid this bias, since diet is assessed before disease onset. Using data from a large, well-defined prospective cohort study, the Iowa Women’s Health Study, we evaluated the relation of vitamins C and E, carotenoids, and antioxidant trace elements with the incidence of rheumatoid arthritis in older women.

MATERIALS AND METHODS

The Iowa Women’s Health Study cohort

Complete details on the design of the Iowa Women’s Health Study that are specific to rheumatoid arthritis have been previously published (18–20). Briefly, in January 1986, a questionnaire was returned by 41,836 randomly selected women aged 55–69 years. Self-reported items on the baseline (1986) questionnaire included demographic data, medical and reproductive history, use of hormone replacement therapy, smoking history, and other lifestyle factors.

Dietary assessment

Diet was assessed in the 1986 baseline survey using a 127-item semiquantitative food frequency questionnaire developed by Willett et al. (21). For each food, a commonly used portion size or unit was specified. Respondents were asked how often, on average, over the past year they had consumed that amount of each food. There were nine possible responses, ranging from “never or less than once per month” to “six or more times per day,” to define the frequency of consumption of that portion size. Women were asked whether they used a multivitamin and, if so, the brand name of the multivitamin as well as the frequency of use. Respondents were also asked about their use of supplements containing only vitamin C, vitamin E, selenium, or zinc, including the range of the dosage used on a daily basis. Finally, respondents were asked whether they used either supplemental copper or β-carotene on a regular basis (no data on dosage or frequency of use). Information on duration of supplement use was not collected.

Daily intake of nutrients was calculated by multiplying the frequency of consumption of each unit of food by the nutrient content of the specified portions, using a database provided by Willett et al. (21), which was based on values obtained from the US Department of Agriculture. Multivitamin brands were coded individually for estimation of intake of vitamins from supplements. The reliability and validity of the food frequency questionnaire has been documented in this cohort (22).

Cohort follow-up and case identification and validation

Follow-up surveys (response rates for living eligible persons) were mailed in 1987 (91 percent), 1989 (89 percent), 1992 (83 percent), and 1997 (79 percent) to update information on residence and to collect additional exposure and outcome data. In the 1992 and 1997 surveys, respondents were asked whether they had ever been told by a doctor that they had rheumatoid arthritis, as well as their age at diagnosis. Of the 35,635 women who responded to the 1992 and/or 1997 survey, 3,171 women were classified as having potential incident cases (first diagnosed after 1986), while 2,012 were classified as having prevalent cases (diagnosed in 1986 or before).

We attempted to validate all potential incident cases (n = 3,171). To do this, we contacted women by mail to confirm their responses, to obtain the names and addresses of all physicians whom they had seen about their rheumatoid arthritis, and to obtain consent for release of their medical records. Reminder postcards were sent after the initial letter, followed by a second mailing. Nonrespondents to this supplemental questionnaire were contacted by telephone. We contacted 98 percent of the eligible women (or next of kin for deceased subjects), and 91 percent of the eligible women participated in the validation survey (2,886/3,171). Of the women contacted, 52 percent (1,659/3,171) were found not to have eligible incident cases, either because rheumatoid arthritis was first diagnosed before January 1, 1987, or because their “not sure” or “yes” response became a “no” after further questioning.

For the 1,227 women confirming a self-reported diagnosis of rheumatoid arthritis, we contacted the identified physicians and asked them to complete a brief questionnaire and to provide all medical, laboratory, and radiographic records pertinent to the diagnosis. Medical records were obtained for 1,186 of these 1,227 women (97 percent). A combination of two trained reviewers independently reviewed all medical records to determine rheumatoid arthritis case status using the “ever” (since cohort baseline) satisfaction of four out of seven American College of Rheumatology (ACR) criteria (morning stiffness, arthritis in three or more joint areas, arthritis of the hand joints, symmetric arthritis, rheumatoid nodules, positivity for serum rheumatoid factor, and radiographic changes) (23). Discordance between the two primary reviewers was adjudicated by consensus. Although medical records were requested for all potential cases, any diagnosis of “definite rheumatoid arthritis” provided by a physician identified as a board-certified/eligible rheumatologist was also considered to constitute a validated case. We defined onset of rheumatoid arthritis as the first date of appearance of an arthritis symptom leading to the eventual satisfaction of ACR criteria or a rheumatologist’s diagnosis. Review of these 1,186 sets of medical records resulted in the accrual of 158 validated cases of rheumatoid arthritis. Diagnosis of rheumatoid arthritis was based on cumulative satisfaction of the ACR criteria and diagnosis by a rheumatologist (n = 127), cumulative satisfaction of ACR criteria alone (n = 20), or diagnosis by a rheumatologist alone (n = 11).

Data analysis

Of the 35,635 women who responded to the 1992 and/or 1997 survey, we excluded women with rheumatoid arthritis first diagnosed before 1987 (n = 2,102; no attempt at validation) and women in the validation survey (i.e., potentially incident cases) who did not meet our validation criteria (n = 2,197); this left 31,336 women in the at-risk cohort. We further excluded 1,968 women (six cases) who left 30 or more food items blank on the questionnaire or had implausible daily energy intakes (i.e., <600 kcal or ≥5,000 kcal); this left 29,368 women and 152 cases in the analysis data set.

Each woman accumulated person-years of follow-up from the date of receipt of the 1986 baseline questionnaire to one of the following (in order of priority): 1) the date of onset of rheumatoid arthritis symptoms; 2) September 30, 1992 (the date of the Follow-up 3 questionnaire), for women who did not complete the Follow-up 4 questionnaire (because of death or nonresponse); or 3) August 31, 1997 (the date of the Follow-up 4 questionnaire), for all remaining women.

Dietary variables were categorized into tertiles based on the distribution of consumption among all women included in the analysis. Relative risks and 95 percent confidence intervals were calculated as measures of association between the dietary factors of interest and rheumatoid arthritis incidence and were estimated using Cox proportional hazards regression (24). In initial models, data were adjusted for age and total energy intake, treating total energy as a continuous covariate in the Cox model. Total energy intake was included in all models to adjust for systematic over- and underreporting of food intake (25). In multivariable models, data were also adjusted for marital status (currently married, widowed, separated/divorced, or never married), smoking history (never smoker, former smoker of <20 pack-years, former smoker of ≥20 pack-years, current smoker of <20 pack-years, or current smoker of ≥20 pack-years), age at menopause (continuous variable), use of estrogen replacement therapy (never, former, or current user), decaffeinated coffee consumption (none, <2, 2–3, or >3 cups/day), and tea consumption (none, <0.6, 0.6–3, or >3 cups/day)—factors that have been associated with rheumatoid arthritis in this cohort (18, 20). Body mass index and alcohol use, which have been associated with rheumatoid arthritis in some studies but not in this cohort (19), were also evaluated but were not confounders in this data set (data not shown).

RESULTS

At study baseline in 1986, there were 29,368 women in the at-risk cohort, and their mean age was 61.4 years. Over 99 percent were White, 79 percent were married, 33 percent had ever smoked, 12 percent were using hormone replacement therapy, 57 percent consumed decaffeinated coffee, and 58 percent consumed tea. During 314,181 person-years of follow-up, there were 152 validated cases of rheumatoid arthritis. The median age at symptom onset was 68 years (range, 57–79 years), and the median time from symptom onset to definitive diagnosis was 1.1 year (range, 0–12.2 years). Of the 152 case women, 62 percent were rheumatoid factor-positive, 31 percent were rheumatoid factor-negative, and 7 percent had missing values. The median time from the 1986 baseline survey to symptom onset in the rheumatoid arthritis cases was 5.9 years (range, 0.9–12 years).

There were weak, statistically nonsignificant inverse associations between intakes of vitamin C (total, food, and supplemental), vitamin E (total and supplemental), and carotenoids (supplemental only) and risk of rheumatoid arthritis, while there was no association for vitamin E or for carotenoids obtained from food (table 1). Table 2 expands the carotenoids into common classes, each of which have differing but overlapping food sources and antioxidant properties. There was no association of α-carotene, β-carotene, lycopene, or lutein/zeaxanthin with risk of rheumatoid arthritis. In contrast, there was an inverse association of β-cryptoxanthin with rheumatoid arthritis risk (p-trend = 0.005) that remained virtually unchanged after adjustment for other arthritis risk factors. Compared with women consuming <40 µg/day, women consuming 40–86.9 µg/day (relative risk (RR) = 0.73, 95 percent confidence interval (CI): 0.49, 1.10) and women consuming >86.9 µg/day (RR = 0.59, 95 percent CI: 0.39, 0.90) were at lower risk of developing rheumatoid arthritis. When supplemental vitamins C and E and β-cryptoxanthin were included in the same model, only β-cryptoxanthin was significantly associated with risk of rheumatoid arthritis, while the initially suggestive associations with the other variables were attenuated.

We next evaluated the role of antioxidant trace elements in risk of rheumatoid arthritis (table 3). Zinc from food and supplements combined was not associated with risk, while there was a suggestive positive association of zinc from the diet (highest tertile only) with rheumatoid arthritis risk and an inverse association of use of zinc supplements; these results remained after adjustment for other arthritis risk factors. Copper and manganese showed similar patterns, in that there was little association between dietary intake of these antioxidant trace elements and risk of rheumatoid arthritis, while any use of copper supplements (RR = 0.54, 95 percent CI: 0.28, 1.03) and any use of manganese supplements (RR = 0.50, 95 percent CI: 0.23, 1.07) were inversely associated with arthritis risk. Use of selenium supplements also showed a suggestive inverse association with arthritis risk (RR = 0.63, 95 percent CI: 0.32, 1.23); we did not have data on selenium from the diet. When supplemental zinc, copper, manganese, and selenium were included the same model, only zinc remained strongly associated with risk of rheumatoid arthritis.

Tables 4 and 5 present results from analyses focused on fruits and vegetables that are the major dietary sources of antioxidants. There was a graded inverse association between risk of rheumatoid arthritis and greater intake of fruits (p-trend = 0.03), although this association was attenuated somewhat after adjustment for other rheumatoid arthritis risk factors (p-trend = 0.13). Citrus fruits, an important source of β-cryptoxanthin, showed a weak inverse association with rheumatoid arthritis that was not statistically significant. Of the food items contributing to the citrus fruit category, only consumption of oranges showed an inverse association with rheumatoid arthritis.

There was a weak inverse trend with intake of vegetables (table 5) that was not statistically significant (p-trend = 0.33). Of the major classes of vegetables evaluated, only cruciferous vegetables showed an inverse association with rheumatoid arthritis, and this association remained after adjustment for other arthritis risk factors. Of the major components in the cruciferous vegetable group, consumption of broccoli showed the strongest inverse association, with approximately a 35 percent lower risk of rheumatoid arthritis appearing at the highest level of intake after adjustment for other arthritis risk factors.

When both fruit consumption and cruciferous vegetable consumption were included in the same model, the relative risks for the upper two categories of fruit intake were 0.79 (95 percent CI: 0.52, 1.19) and 0.77 (95 percent CI: 0.49, 1.21), and the risks for the upper two categories of cruciferous vegetable intake were 0.75 (95 percent CI: 0.49, 1.15) and 0.69 (95 percent CI: 0.44, 1.08). Neither trend test gave a significant result (p = 0.25 and p = 0.12, respectively).

We next included both zinc supplements and β-cryptoxanthin in the same model, a model that also controlled for the other rheumatoid arthritis risk factors; both variables remained statistically significant predictors. For zinc supplements, the relative risks for the upper two categories of intake were 0.95 (95 percent CI: 0.50, 1.81) and 0.40 (95 percent CI: 0.18, 0.90), and the trend test was significant (p = 0.03). For β-cryptoxanthin, the relative risks were 0.74 (95 percent CI: 0.49, 1.11) and 0.62 (95 percent CI: 0.40, 0.94), and the trend test was significant (p = 0.02). When we repeated these analyses with the data stratified according to baseline smoking history (ever/never), the inverse associations for β-cryptoxanthin and supplemental zinc were similar in each smoking stratum, providing no evidence of effect modification by smoking.

DISCUSSION

We found strong inverse associations between intakes of β-cryptoxanthin and supplemental zinc and risk of rheumatoid arthritis in this cohort of older women. These associations held after adjustment for other risk factors for rheumatoid arthritis in this cohort, including cigarette smoking (risk factor) and tea consumption (protective factor), and were independent of each other. However, zinc intake from the diet showed a suggestive positive association with risk. Supplemental vitamin C, supplemental vitamin E, copper, manganese, and selenium showed suggestive inverse trends that were attenuated after adjustment for β-cryptoxanthin and/or supplemental zinc. The strongest findings from an analysis of food groups were inverse associations with greater consumption of fruits and cruciferous vegetables, although neither association was statistically significant after multivariate adjustment.

Strengths of this study include the prospective cohort design, the rigorous case validation using ACR criteria, the community setting, and the use of a validated food frequency questionnaire. We were also able to adjust for other rheumatoid arthritis risk factors that could potentially confound any dietary associations, particularly marital status and smoking history.

On the other hand, inaccurate measurement of diet is likely to have been an important source of error in this study. Measurement error is further increased by the processing, storage, and handling of foods, both during manufacture and during preparation at home (26, 27). However, given the cohort design, this error should have been random with respect to the future development of rheumatoid arthritis; therefore, it would be expected to decrease the ability to detect associations (28). In addition, we assessed diet with only a single questionnaire at baseline, and thus we were unable to incorporate changes in diet into our analysis, including secular changes in dietary patterns among cohort members. However, given the high potential for dietary change in response to the clinical onset of rheumatoid arthritis and its treatment, data on a person’s diet in the more remote past (reflective of usual adult patterns) may be of greater validity.

This study had other potential limitations. The cohort consisted mainly of White, older women from the Midwest, and this may limit generalizability. Some studies have suggested that elderly-onset rheumatoid arthritis, compared with younger-onset arthritis, may have a distinct clinical presentation (e.g., abrupt onset, absence of serum rheumatoid factor, less common occurrence of subcutaneous nodules) and may also involve a poorer outcome and faster functional decline (29–31), although this remains controversial. In addition, while the presentation and outcome of elderly-onset rheumatoid arthritis may differ from that of younger-onset arthritis, there is currently no evidence that environmental risk factors per se operate differently, although there is some evidence that the relative role of nongenetic factors may be somewhat greater in elderly-onset arthritis (32, 33).

There was an opportunity for nonresponse during the various phases of follow-up conducted to identify and validate rheumatoid arthritis cases in the cohort, which could have introduced bias. However, we had high response rates in each phase of the study, and thus it seems unlikely that this would have introduced a large, systematic bias into our results. Another potential weakness relates to the fact that we did not clinically examine each case patient. However, given the rigorous case validation methods, it seems highly unlikely that we incorrectly classified subjects as arthritis cases. Conversely, it is possible that individuals with milder rheumatoid arthritis or those not seeking medical attention were misclassified; however, the large group of noncases used for the comparison group makes false negatives less of a concern in this analysis.

Vitamins C and E and carotenoids

Vitamins C and E and provitamin A carotenoids are strong antioxidants and have been hypothesized to protect against the development of rheumatoid arthritis (12). A nested case-control study conducted in Finland (13) found that people with incident cases of rheumatoid arthritis (n = 27) had lower prediagnostic serum levels of α-tocopherol (9 percent lower, p = 0.29) and β-carotene (28 percent lower, p = 0.12) than matched controls (n = 51). After additional follow-up (122 cases, 357 controls), serum levels of α-tocopherol were only 1.4 percent lower in cases, while results for β-carotene were not reported (34). A nested case-control study conducted in Maryland (14) found that persons with incident cases of rheumatoid arthritis (n = 21) had lower prediagnostic serum levels of α-tocopherol (5 percent lower, p > 0.05) and β-carotene (29 percent lower, p < 0.05) than matched controls (n = 84). In a population-based case-control study of 324 arthritis cases aged 18–64 years and 1,245 controls (15), there was no association of rheumatoid arthritis with dietary vitamin E, and there was a weak inverse association with dietary vitamin C (for the highest quartile vs. the lowest, RR = 0.82, 95 percent CI: 0.56, 1.20).

Our results are broadly consistent with these studies suggesting a weak protective role at best for vitamins C and E in the etiology of rheumatoid arthritis. Our results are not consistent with the two Finnish nested case-control studies that reported an inverse association with serum β-carotene (13, 34). To our knowledge, no previous studies have specifically evaluated relations between other carotenoids (serum or dietary) and risk of rheumatoid arthritis. Our finding of a protective association with β-cryptoxanthin is novel and, if replicated, of high importance. There is reasonably strong correlation between estimated β-cryptoxanthin intake from a food frequency questionnaire and blood concentrations (r = 0.4–0.5) (35–37), and β-cryptoxanthin is a relatively strong antioxidant (38, 39). β-Cryptoxanthin is mainly derived from citrus fruits, although in our data only consumption of oranges and, more weakly, grapefruit juice (but not orange juice or grapefruit) was inversely associated with rheumatoid arthritis. Thus, it may be that other substances in fruits or vegetables, particularly in oranges, are primarily responsible for the inverse association observed for β-cryptoxanthin.

Trace elements

The efficacy of zinc and selenium supplementation in the treatment of rheumatoid arthritis has long been debated (4, 12). However, to our knowledge, there is only a single epidemiologic study that has specifically addressed the role of antioxidant trace elements in the etiology of rheumatoid arthritis. In extended follow-up of the Finnish nested case-control study population discussed above (34), prediagnostic serum selenium levels were inversely associated with risk of rheumatoid arthritis (for highest tertile vs. lowest, odds ratio = 0.65, 95 percent CI: 0.36, 1.16), particularly rheumatoid factor-negative rheumatoid arthritis (for highest tertile vs. lowest, odds ratio = 0.16, 95 percent CI: 0.04, 0.69). The inverse association of rheumatoid arthritis with supplemental selenium in our data, although not statistically significant and weaker than the associations for other antioxidant trace elements, is consistent with the Finnish study, although it must be acknowledged that we were not able to assess dietary selenium in our analyses. Selenium is an essential trace element and is utilized by glutathione peroxidase, which is a crucial enzyme for cellular defense against toxic free radicals (4).

To our knowledge, no prior studies have evaluated zinc, copper, or manganese as a risk factor for rheumatoid arthritis. We found inverse associations with supplemental intake of these micronutrients but found no association from dietary estimates, and for zinc we actually found a suggestive positive association with risk. This complicates interpretation of the findings, since it is not clear whether the inverse association with supplements is from higher levels achieved by use of supplements, an artifact of measurement (less accurate assessment of dietary intake for these micronutrients), residual confounding by some other health behavior, or a chance finding. Zinc is essential for normal growth and immunologic function and is found in a wide variety of enzymes. Zinc is a potent inducer of metallothionine, which then acquires zinc or copper as a cofactor and functions as an intracellular oxygen radical scavenger (4). Zinc is also a cofactor in collagen synthesis (12). Levels of copper and ceruloplasmin (to which 90 percent of copper is bound) increase with rheumatoid arthritis disease activity, and this is thought to represent a protective response, since ceruloplasmin acts as an antioxidant (4, 10). Copper and zinc are also cofactors for cytosolic superoxide dismutase; this enzyme detoxifies superoxide radicals produced by activated macrophages (4).

Fruits and vegetables

While the above discussion has focused on specific antioxidant micronutrients and the foods in which they are commonly found, more globally we found suggestive inverse associations for diets high in fruits and cruciferous vegetables. In a population-based case-control study that used an extensive food frequency questionnaire (15), there was a weak inverse association for intake of fruit (for highest quartile vs. lowest, odds ratio = 0.88, 95 percent CI: 0.61, 1.26) but no association for intake of vegetables. In a hospital-based case-control study (16) conducted in Greece, consumption of cooked vegetables was strongly and inversely related to rheumatoid arthritis risk (for highest quartile vs. lowest, odds ratio = 0.39, 95 percent CI: 0.19, 0.82), while the association for consumption of raw vegetables was much weaker (odds ratio = 0.85, 95 percent CI: 0.44, 1.67). Neither of these studies reported data for subclasses of vegetables (e.g., cruciferous vegetables).

Summary

Results from this prospective cohort study support the hypothesis that intake of certain antioxidant micronutrients, particularly β-cryptoxanthin and supplemental zinc, may protect against the development of rheumatoid arthritis. If these findings are confirmed with additional epidemiologic and mechanistic data, this would represent one of the few potentially modifiable protective factors for this serious chronic disease.

ACKNOWLEDGMENTS

This study was supported by a Clinical Science Grant from the Arthritis Foundation. The Iowa Women’s Health Study was supported by National Cancer Institute grant R01 CA39741.

The authors thank Dr. Aaron R. Folsom for assistance with the study design and Mary Jo Janisch for assistance with manuscript preparation.

Correspondence to Dr. James R. Cerhan, Department of Health Sciences Research, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 (e-mail: cerhan.james@mayo.edu).

TABLE 1.

Relative risk of rheumatoid arthritis according to intake of antioxidant vitamins from food and supplements, Iowa Women’s Health Study, 1986–1997

Micronutrient No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
Vitamin C (mg/day)          
Total          
<145 63 103,664 1.00‡    1.00   
145–251 38 103,934 0.60 0.40, 0.91   0.63 0.41, 0.96  
>251 51 106,583 0.77 0.53, 1.13 0.18  0.72 0.48, 1.09 0.11 
Food only          
<116 59 103,270 1.00    1.00   
116–169 50 104,022 0.82 0.56, 1.20   0.86 0.57, 1.30  
>169 43 106,889 0.69 0.45, 1.06 0.09  0.75 0.48, 1.18 0.21 
Supplements only          
Nonusers 93 173,742 1.00    1.00   
<159 28 70,104 0.75 0.49, 1.14   0.76 0.49, 1.18  
≥159 31 70,336 0.80 0.53, 1.20 0.18  0.70 0.45, 1.09 0.08 
Vitamin E (IU/day)          
Total          
<8.6 50 100,858 1.00    1.00   
8.6–20.1 56 106,358 1.13 0.74, 1.72   1.19 0.76, 1.85  
>20.1 46 106,965 0.88 0.58, 1.34 0.49  0.85 0.54, 1.33 0.41 
Food only          
<7.3 54 102,323 1.00    1.00   
7.3–10.0 46 102,021 0.89 0.58, 1.35   0.92 0.59, 1.43  
>10.0 52 109,837 0.95 0.57, 1.58 0.83  0.99 0.58, 1.69 0.96 
Supplements only          
Nonusers 108 199,450 1.00    1.00   
<30 13 45,976 0.52 0.29, 0.93   0.52 0.2, 0.95  
≥30 31 68,755 0.80 0.54, 1.21 0.13  0.72 0.47, 1.12 0.06 
Carotenoids (IU/day)          
Total          
<5,357 50 103,390 1.00    1.00   
5,357–10,400 49 103,703 0.98 0.65, 1.46   0.98 0.64, 1.49  
>10,400 53 107,088 1.07 0.71, 1.61 0.76  1.08 0.70, 1.67 0.73 
Food only          
<5,154 54 103,390 1.00    1.00   
5,154–10,078 44 103,703 0.84 0.56, 1.27   0.78 0.51, 1.20  
>10,078 54 107,088 1.02 0.68, 1.53 0.92  1.02 0.65, 1.53 0.99 
Supplements only          
Nonusers 142 283,152 1.00    1.00   
Users 10 31,029 0.58 0.30, 1.14 0.11  0.63 0.32, 1.25 0.19 
Micronutrient No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
Vitamin C (mg/day)          
Total          
<145 63 103,664 1.00‡    1.00   
145–251 38 103,934 0.60 0.40, 0.91   0.63 0.41, 0.96  
>251 51 106,583 0.77 0.53, 1.13 0.18  0.72 0.48, 1.09 0.11 
Food only          
<116 59 103,270 1.00    1.00   
116–169 50 104,022 0.82 0.56, 1.20   0.86 0.57, 1.30  
>169 43 106,889 0.69 0.45, 1.06 0.09  0.75 0.48, 1.18 0.21 
Supplements only          
Nonusers 93 173,742 1.00    1.00   
<159 28 70,104 0.75 0.49, 1.14   0.76 0.49, 1.18  
≥159 31 70,336 0.80 0.53, 1.20 0.18  0.70 0.45, 1.09 0.08 
Vitamin E (IU/day)          
Total          
<8.6 50 100,858 1.00    1.00   
8.6–20.1 56 106,358 1.13 0.74, 1.72   1.19 0.76, 1.85  
>20.1 46 106,965 0.88 0.58, 1.34 0.49  0.85 0.54, 1.33 0.41 
Food only          
<7.3 54 102,323 1.00    1.00   
7.3–10.0 46 102,021 0.89 0.58, 1.35   0.92 0.59, 1.43  
>10.0 52 109,837 0.95 0.57, 1.58 0.83  0.99 0.58, 1.69 0.96 
Supplements only          
Nonusers 108 199,450 1.00    1.00   
<30 13 45,976 0.52 0.29, 0.93   0.52 0.2, 0.95  
≥30 31 68,755 0.80 0.54, 1.21 0.13  0.72 0.47, 1.12 0.06 
Carotenoids (IU/day)          
Total          
<5,357 50 103,390 1.00    1.00   
5,357–10,400 49 103,703 0.98 0.65, 1.46   0.98 0.64, 1.49  
>10,400 53 107,088 1.07 0.71, 1.61 0.76  1.08 0.70, 1.67 0.73 
Food only          
<5,154 54 103,390 1.00    1.00   
5,154–10,078 44 103,703 0.84 0.56, 1.27   0.78 0.51, 1.20  
>10,078 54 107,088 1.02 0.68, 1.53 0.92  1.02 0.65, 1.53 0.99 
Supplements only          
Nonusers 142 283,152 1.00    1.00   
Users 10 31,029 0.58 0.30, 1.14 0.11  0.63 0.32, 1.25 0.19 

* Adjusted for age, total energy intake, marital status, smoking history, age at menopause, use of hormone replacement therapy, decaffeinated coffee consumption, and tea consumption.

† RR, relative risk; CI, confidence interval.

‡ Reference category.

TABLE 2.

Relative risk of rheumatoid arthritis according to intake of selected carotenoids, Iowa Women’s Health Study, 1986–1997

Carotenoid No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
α-Carotene (µg/day)          
<428 52 103,117 1.00‡    1.00   
428–751 48 103,967 0.95 0.64, 1.41   0.98 0.65, 1.48  
>751 52 107,097 1.01 0.67, 1.51 0.96  1.02 0.66, 1.56 0.95 
β-Carotene (µg/day)          
<3,000 51 103,428 1.00    1.00   
3,000–5,307 52 103,778 1.01 0.68, 1.49   0.98 0.65, 1.49  
>5,307 49 106,975 0.95 0.63, 1.45 0.83  0.97 0.62, 1.50 0.88 
β-Cryptoxanthin (µg/day)          
<40.0 66 102,131 1.00    1.00   
40.0–86.9 43 97,358 0.67 0.45, 0.98   0.73 0.49, 1.10  
>86.9 43 114,692 0.58 0.39, 0.85 0.005  0.59 0.39, 0.90 0.01 
Lycopene (µg/day)          
<2,647 56 102,878 1.00    1.00   
2,647–4,640 50 104,342 0.86 0.59, 1.27   0.89 0.59, 1.34  
>4,640 46 106,961 0.79 0.53, 1.19 0.26  0.77 0.50, 1.18 0.23 
Lutein + zeaxanthin (µg/day)          
<1,713 52 103,715 1.00    1.00   
1,713–3,081 50 103,965 0.99 0.67, 1.47   0.90 0.60, 1.37  
>3,081 50 106,501 0.98 0.65, 1.48 0.93  0.92 0.60, 1.42 0.71 
Carotenoid No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
α-Carotene (µg/day)          
<428 52 103,117 1.00‡    1.00   
428–751 48 103,967 0.95 0.64, 1.41   0.98 0.65, 1.48  
>751 52 107,097 1.01 0.67, 1.51 0.96  1.02 0.66, 1.56 0.95 
β-Carotene (µg/day)          
<3,000 51 103,428 1.00    1.00   
3,000–5,307 52 103,778 1.01 0.68, 1.49   0.98 0.65, 1.49  
>5,307 49 106,975 0.95 0.63, 1.45 0.83  0.97 0.62, 1.50 0.88 
β-Cryptoxanthin (µg/day)          
<40.0 66 102,131 1.00    1.00   
40.0–86.9 43 97,358 0.67 0.45, 0.98   0.73 0.49, 1.10  
>86.9 43 114,692 0.58 0.39, 0.85 0.005  0.59 0.39, 0.90 0.01 
Lycopene (µg/day)          
<2,647 56 102,878 1.00    1.00   
2,647–4,640 50 104,342 0.86 0.59, 1.27   0.89 0.59, 1.34  
>4,640 46 106,961 0.79 0.53, 1.19 0.26  0.77 0.50, 1.18 0.23 
Lutein + zeaxanthin (µg/day)          
<1,713 52 103,715 1.00    1.00   
1,713–3,081 50 103,965 0.99 0.67, 1.47   0.90 0.60, 1.37  
>3,081 50 106,501 0.98 0.65, 1.48 0.93  0.92 0.60, 1.42 0.71 

*Adjusted for age, total energy intake, marital status, smoking history, age at menopause, use of hormone replacement therapy, decaffeinated coffee consumption, and tea consumption.

† RR, relative risk; CI, confidence interval.

‡ Reference category.

TABLE 3.

Relative risk of rheumatoid arthritis according to intake of antioxidant micronutrients, Iowa Women’s Health Study, 1986–1997

Trace element No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
Zinc (mg/day)          
Total          
<10.4 52 103,100 1.00‡    1.00   
10.4–15.5 47 104,156 0.92 0.60, 1.41   0.86 0.54, 1.35  
>15.5 53 106,925 1.01 0.64, 1.61 0.94  1.02 0.63, 1.66 0.88 
Food only          
<9.7 50 103,162 1.00    1.00   
9.7–13.5 40 103,889 0.94 0.60, 1.48   0.88 0.55, 1.42  
>13.5 62 107,130 1.69 1.00, 2.85 0.05  1.66 0.96, 2.85 0.07 
Supplements only          
Nonusers 133 257,742 1.00    1.00   
<15 12 22,967 1.02 0.56, 1.83   0.94 0.49, 1.79  
≥15 33,472 0.62 0.15, 0.79 0.02  0.39 0.17, 0.88 0.03 
Copper (mg/day)          
Total          
<1.16 58 103,186 1.00    1.00   
1.16–1.70 38 102,996 0.66 0.43, 1.02   0.69 0.44, 1.09  
>1.70 56 107,999 0.92 0.59, 1.44 0.74  0.98 0.62, 1.57 0.98 
Food only          
<1.10 54 102,361 1.00    1.00   
1.10–1.56 44 104,176 0.85 0.55, 1.29   0.92 0.59, 1.43  
>1.56 54 107,644 1.05 0.65, 1.70 0.86  1.15 0.69, 1.91 0.59 
Supplements only          
Nonusers 140 274,345 1.00    1.00    
Users 12 39,836 0.54 0.29, 1.00 0.05  0.54 0.28, 1.03 0.06 
Manganese (mg/day)          
Total          
<2.14 59 100,778 1.00    1.00   
2.14–3.17 45 105,156 0.71 0.47, 1.07   0.79 0.51, 1.22  
>3.17 48 108,247 0.70 0.45, 1.11 0.13  0.86 0.54, 1.39 0.56 
Food only          
<2.09 57 103,283 1.00    1.00   
2.09–3.00 46 103,629 0.82 0.54, 1.23   0.93 0.60, 1.44  
>3.00 49 107,269 0.84 0.52, 1.35 0.46  1.07 0.65, 1.77 0.79 
Supplements only          
Nonusers 144 284,172 1.00    1.00   
Users 30,009 0.46 0.22, 0.98 0.04  0.50 0.23, 1.07 0.08 
Selenium supplements          
Nonusers 141 282,716 1.00    1.00   
Users 11 31,465 0.64 0.34, 1.21 0.17  0.63 0.32, 1.23 0.17 
Trace element No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
Zinc (mg/day)          
Total          
<10.4 52 103,100 1.00‡    1.00   
10.4–15.5 47 104,156 0.92 0.60, 1.41   0.86 0.54, 1.35  
>15.5 53 106,925 1.01 0.64, 1.61 0.94  1.02 0.63, 1.66 0.88 
Food only          
<9.7 50 103,162 1.00    1.00   
9.7–13.5 40 103,889 0.94 0.60, 1.48   0.88 0.55, 1.42  
>13.5 62 107,130 1.69 1.00, 2.85 0.05  1.66 0.96, 2.85 0.07 
Supplements only          
Nonusers 133 257,742 1.00    1.00   
<15 12 22,967 1.02 0.56, 1.83   0.94 0.49, 1.79  
≥15 33,472 0.62 0.15, 0.79 0.02  0.39 0.17, 0.88 0.03 
Copper (mg/day)          
Total          
<1.16 58 103,186 1.00    1.00   
1.16–1.70 38 102,996 0.66 0.43, 1.02   0.69 0.44, 1.09  
>1.70 56 107,999 0.92 0.59, 1.44 0.74  0.98 0.62, 1.57 0.98 
Food only          
<1.10 54 102,361 1.00    1.00   
1.10–1.56 44 104,176 0.85 0.55, 1.29   0.92 0.59, 1.43  
>1.56 54 107,644 1.05 0.65, 1.70 0.86  1.15 0.69, 1.91 0.59 
Supplements only          
Nonusers 140 274,345 1.00    1.00    
Users 12 39,836 0.54 0.29, 1.00 0.05  0.54 0.28, 1.03 0.06 
Manganese (mg/day)          
Total          
<2.14 59 100,778 1.00    1.00   
2.14–3.17 45 105,156 0.71 0.47, 1.07   0.79 0.51, 1.22  
>3.17 48 108,247 0.70 0.45, 1.11 0.13  0.86 0.54, 1.39 0.56 
Food only          
<2.09 57 103,283 1.00    1.00   
2.09–3.00 46 103,629 0.82 0.54, 1.23   0.93 0.60, 1.44  
>3.00 49 107,269 0.84 0.52, 1.35 0.46  1.07 0.65, 1.77 0.79 
Supplements only          
Nonusers 144 284,172 1.00    1.00   
Users 30,009 0.46 0.22, 0.98 0.04  0.50 0.23, 1.07 0.08 
Selenium supplements          
Nonusers 141 282,716 1.00    1.00   
Users 11 31,465 0.64 0.34, 1.21 0.17  0.63 0.32, 1.23 0.17 

*Adjusted for age, total energy intake, marital status, smoking history, age at menopause, use of hormone replacement therapy, decaffeinated coffee consumption, and tea consumption.

† RR, relative risk; CI, confidence interval.

‡ Reference category.

TABLE 4.

Relative risk of rheumatoid arthritis according to intake of all fruits and selected fruits, Iowa Women’s Health Study, 1986–1997

Fruit (servings per month) No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
All fruits          
<52 61 98,306 1.00‡    1.00   
52–83 48 108,149 0.70 0.47, 1.02   0.75 0.50, 1.13  
>83 43 107,726 0.63 0.42, 0.96 0.03  0.72 0.46, 1.12 0.13 
Citrus fruits          
<16 57 99,751 1.00    1.00   
16–32 43 101,941 0.74 0.50, 1.10   0.80 0.53, 1.21  
>32 52 112,489 0.80 0.55, 1.18 0.26  0.84 0.56, 1.27 0.40 
Oranges          
42 70,669 1.00    1.00   
1–4 67 131,430 0.88 0.59, 1.29   0.96 0.64, 1.45  
>4 43 112,082 0.66 0.43, 1.02 0.06  0.69 0.43, 1.10 0.10 
Orange juice          
37 72,907 1.00    1.00   
1–12 64 137,822 0.92 0.61, 1.38   1.05 0.68, 1.63  
>12 51 103,452 0.97 0.63, 1.49 0.92  1.11 0.70, 1.77 0.64 
Grapefruit          
54 117,919 1.00    1.00   
1–3 38 65,398 1.30 0.86, 1.97   1.46 0.94, 2.27  
>3 60 130,864 1.03 0.71, 1.50 0.90  1.12 0.75, 1.66 0.62 
Grapefruit juice          
126 249,044 1.00    1.00   
>0 26 65,137 0.76 0.50, 1.17 0.21  0.75 0.48, 1.18 0.21 
Fruit (servings per month) No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
All fruits          
<52 61 98,306 1.00‡    1.00   
52–83 48 108,149 0.70 0.47, 1.02   0.75 0.50, 1.13  
>83 43 107,726 0.63 0.42, 0.96 0.03  0.72 0.46, 1.12 0.13 
Citrus fruits          
<16 57 99,751 1.00    1.00   
16–32 43 101,941 0.74 0.50, 1.10   0.80 0.53, 1.21  
>32 52 112,489 0.80 0.55, 1.18 0.26  0.84 0.56, 1.27 0.40 
Oranges          
42 70,669 1.00    1.00   
1–4 67 131,430 0.88 0.59, 1.29   0.96 0.64, 1.45  
>4 43 112,082 0.66 0.43, 1.02 0.06  0.69 0.43, 1.10 0.10 
Orange juice          
37 72,907 1.00    1.00   
1–12 64 137,822 0.92 0.61, 1.38   1.05 0.68, 1.63  
>12 51 103,452 0.97 0.63, 1.49 0.92  1.11 0.70, 1.77 0.64 
Grapefruit          
54 117,919 1.00    1.00   
1–3 38 65,398 1.30 0.86, 1.97   1.46 0.94, 2.27  
>3 60 130,864 1.03 0.71, 1.50 0.90  1.12 0.75, 1.66 0.62 
Grapefruit juice          
126 249,044 1.00    1.00   
>0 26 65,137 0.76 0.50, 1.17 0.21  0.75 0.48, 1.18 0.21 

*Adjusted for age, total energy intake, marital status, smoking history, age at menopause, use of hormone replacement therapy, decaffeinated coffee consumption, and tea consumption.

† RR, relative risk; CI, confidence interval.

‡ Reference category.

TABLE 5.

Relative risk of rheumatoid arthritis according to intake of all vegetables and selected vegetables, Iowa Women’s Health Study, 1986–1997

Vegetable (servings per month) No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
All vegetables          
<60 57 99,739 1.00‡    1.00   
60–97 45 107,016 0.72 0.48, 1.08   0.66 0.43, 1.00  
>97 50 107,426 0.82 0.55, 1.24 0.33  0.74 0.48, 1.14 0.16 
Green leafy vegetables          
<8 47 95,894 1.00    1.00   
8–16 60 114,605 1.06 0.72, 1.55   0.98 0.66, 1.48  
>16 45 103,682 0.90 0.59, 1.36 0.61  0.89 0.57, 1.37 0.59 
Legumes          
<8 49 95,517 1.00    1.00   
8–13 52 107,573 0.97 0.65, 1.45   1.00 0.66, 1.52  
>13 51 111,091 0.94 0.62, 1.42 0.76  0.95 0.61, 1.48 0.82 
Yellow vegetables          
<5 59 118,558 1.00    1.00   
5–10 38 84,401 0.94 0.62, 1.41   0.83 0.54, 1.29  
>10 55 111,222 1.04 0.71, 1.53 0.84  0.99 0.66, 1.48 0.93 
Cruciferous vegetables           
<6 40 63,421 1.00    1.00   
6–11 58 123,407 0.76  0.51, 1.15   0.73  0.48, 1.12  
>11 54 127,353 0.69  0.46, 1.05 0.10  0.65  0.42, 1.01 0.07 
Cabbage          
<2 28 49,747 1.00    1.00   
2–3 69 137,966 0.88 0.57, 1.37   0.77 0.49, 1.20  
>3 55 126,468 0.78 0.49, 1.25 0.29  0.71 0.44, 1.15 0.20 
Cauliflower          
<2 30 62,583 1.00    1.00   
2–3 76 134,254 1.22 0.79, 1.87   1.20 0.76, 1.88  
>3 46 117,344 0.85 0.53, 1.35 0.32  0.83 0.51, 1.37 0.30 
Broccoli          
<2 34 54,053 1.00    1.00   
2–3 49 96,018 0.83 0.54, 1.30   0.76 0.48, 1.22  
>3 69 164,110 0.69 0.46, 1.05 0.07  0.65 0.42, 1.00 0.07 
Vegetable (servings per month) No. of cases Person-years of follow-up Model adjusting for age and energy intake  Model also adjusting for other rheumatoid arthritis risk factors* 
RR† 95% CI† p-trend  RR 95% CI p-trend 
All vegetables          
<60 57 99,739 1.00‡    1.00   
60–97 45 107,016 0.72 0.48, 1.08   0.66 0.43, 1.00  
>97 50 107,426 0.82 0.55, 1.24 0.33  0.74 0.48, 1.14 0.16 
Green leafy vegetables          
<8 47 95,894 1.00    1.00   
8–16 60 114,605 1.06 0.72, 1.55   0.98 0.66, 1.48  
>16 45 103,682 0.90 0.59, 1.36 0.61  0.89 0.57, 1.37 0.59 
Legumes          
<8 49 95,517 1.00    1.00   
8–13 52 107,573 0.97 0.65, 1.45   1.00 0.66, 1.52  
>13 51 111,091 0.94 0.62, 1.42 0.76  0.95 0.61, 1.48 0.82 
Yellow vegetables          
<5 59 118,558 1.00    1.00   
5–10 38 84,401 0.94 0.62, 1.41   0.83 0.54, 1.29  
>10 55 111,222 1.04 0.71, 1.53 0.84  0.99 0.66, 1.48 0.93 
Cruciferous vegetables           
<6 40 63,421 1.00    1.00   
6–11 58 123,407 0.76  0.51, 1.15   0.73  0.48, 1.12  
>11 54 127,353 0.69  0.46, 1.05 0.10  0.65  0.42, 1.01 0.07 
Cabbage          
<2 28 49,747 1.00    1.00   
2–3 69 137,966 0.88 0.57, 1.37   0.77 0.49, 1.20  
>3 55 126,468 0.78 0.49, 1.25 0.29  0.71 0.44, 1.15 0.20 
Cauliflower          
<2 30 62,583 1.00    1.00   
2–3 76 134,254 1.22 0.79, 1.87   1.20 0.76, 1.88  
>3 46 117,344 0.85 0.53, 1.35 0.32  0.83 0.51, 1.37 0.30 
Broccoli          
<2 34 54,053 1.00    1.00   
2–3 49 96,018 0.83 0.54, 1.30   0.76 0.48, 1.22  
>3 69 164,110 0.69 0.46, 1.05 0.07  0.65 0.42, 1.00 0.07 

*Adjusted for age, total energy intake, marital status, smoking history, age at menopause, use of hormone replacement therapy, decaffeinated coffee consumption, and tea consumption.

† RR, relative risk; CI, confidence interval.

‡ Reference category.

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