Purpose
To explore the association between consumption of fruits and vegetables and the presence of glaucoma in older African-American women.
Design
Cross-sectional study.
Methods
Disc photographs and suprathreshold visual fields were obtained from the 662 African-American participants in the Study of Osteoporotic Fractures. Masked, trained readers graded all discs, and 2 glaucoma specialists reviewed photographs and visual fields. The Block Food Frequency Questionnaire assessed food consumption. Relationships between selected fruit/vegetable/nutrient consumption and glaucoma were evaluated using logistic regression models after adjusting for potential confounders.
Results
After excluding women missing Food Frequency Questionnaire and disc data, 584 African-American women (88.2% of total African-American cohort) were included. Glaucoma was diagnosed in at least 1 eye in 77 subjects (13%). Women who ate 3 or more servings/day of fruits/fruit juices were 79% (odds ratio [OR] = 0.21; 95% confidence interval [CI]: 0.08–0.60) less likely to have glaucoma than women who ate less than 1 serving/day. Women who consumed more than 2 servings/week of fresh oranges (OR = 0.18; 95% CI: 0.06–0.51) and peaches (OR = 0.30; 95% CI: 0.13–0.67) had a decreased odds of glaucoma compared to those consuming less than 1 serving/week. For vegetables, >1 serving/week compared to ≤1 serving/month of collard greens/kale decreased the odds of glaucoma by 57% (OR = 0.43; 95% CI: 0.21–0.85). There was a protective trend against glaucoma in those consuming more fruit/fruit juices ( P = .023), fresh oranges ( P = .002), fresh peaches ( P = .002), and collard greens/kale ( P = .014). Higher consumption of carrots ( P = .061) and spinach ( P = .094) also showed some associations. Individual nutrient intake from food sources found protective trends with higher intakes of vitamin A ( P = .011), vitamin C ( P = .018), and α-carotene ( P = .021), and close to statistically significant trends with β-carotene ( P = .052), folate ( P = .056), and lutein/zeaxanthin ( P = .077).
Conclusion
Higher intake of certain fruits and vegetables high in vitamins A and C and carotenoids may be associated with a decreased likelihood of glaucoma in older African-American women. Randomized controlled trials are needed to determine whether the intake of specific nutrients changes the risk of glaucoma.
Presently, the only treatment shown to prevent progression of glaucoma is lowering of intraocular pressure (IOP), although it does not prevent progression and/or onset in all patients. A primary prevention strategy for glaucoma is highly desirable. Epidemiologic studies on antioxidants, ingested through diet and supplements, have suggested benefit on the risk of multiple diseases, including late age-related macular degeneration, cataract, cardiovascular disease, and cancers, although data are still needed from randomized controlled trials for cataracts, cardiovascular disease, and cancer. In vitro evidence suggests that oxidative stress may contribute to the etiology and progression of glaucoma via apoptosis and extracellular matrix remodeling of the trabecular meshwork and lamina cribosa. It is biologically feasible that antioxidants found in the diet through fruits and vegetables may modify the risk of glaucoma development and/or progression.
We previously investigated associations between diet and glaucoma in a random sample of women from the Study of Osteoporotic Fractures. Some associations, such as that between green leafy vegetables and glaucoma, appeared stronger in the African-American subgroup; however, the number of African-American women in the sample was very small (n = 144, 12.5% of study population). In this study, we further investigated a possible association between glaucoma and the consumption of fruits and vegetables in the entire cohort of African-American women aged 65 and older (n = 662) participating in the Study of Osteoporotic Fractures. The association between the antioxidant constituents of fruits and vegetables and glaucoma was also examined.
Methods
Setting and Subjects
The subjects and setting of the Study of Osteoporotic Fractures have been previously described. Institutional Review Board approvals were obtained from the participating institutions prior to this study in order to review de-identified data that had been collected as part of the Study of Osteoporotic Fractures. The characteristics of the entire study population have been described in earlier reports.
Glaucoma (Outcome Measurement) Ascertainment
The ascertainment of glaucoma has been previously described. In brief, optic nerve images were obtained with a Canon nonmydriatic camera (Canon CR – 45UAF 45-degree autofocus nonmydriatic camera; Canon Inc, Kanagawaken, Japan) through a pharmacologically dilated pupil. Visual field testing was performed on each eye using the Humphrey Field Analyzer suprathreshold 76-point 30-degree visual field test (Carl Zeiss Meditec, Dublin, California). Photographs were graded by 2 masked, trained photograph graders. The visual fields and photographs of all women with a cup-to-disc ratio of 0.6 or greater (n = 118), asymmetry between vertical cup-to-disc ratios of 0.2 or greater (n = 93), discrepancy greater than 0.1 between photograph graders on the grading of cup-to-disc ratios (n = 161), and/or discrepancy in notation of focal thinning/notching of the neuroretinal rim between photograph graders (n = 62), along with a 5% random sample of the women with cup-to-disc ratios less than 0.6 (n = 36), were evaluated by a masked, trained glaucoma specialist (J.G.). The optic nerves were diagnosed as glaucomatous based on diffuse or localized thinning of the neuroretinal rim and loss of retinal nerve fiber layer. Visual field loss was defined as the presence of at least 1 missing point on the suprathreshold test. A second glaucoma specialist (A.C.) reviewed all optic nerves diagnosed with glaucoma and glaucoma suspect, along with the 5% random sample for confirmation of the diagnosis.
Measurement of Fruit/Vegetable Consumption and Antioxidant Intake
Consumption of fruits and vegetables was assessed using the 1995 Block Food Frequency Questionnaire. The Block questionnaire is a validated, self-administered diet questionnaire developed from the National Health and Nutrition Survey III (or NHANES III) that asks for average frequency of food intake over the last year. Participants completed the questionnaire just before their clinical visit. Block Dietary Data Systems (Berkeley, California, USA) calculated nutrition summary variables based on questionnaire responses, including daily intake of vitamins, fat, protein, carbohydrates, and nutrients obtained from all food sources (not including intake from supplements).
Statistical Analysis
Excluded from the analysis were women with incomplete questionnaires or unknown glaucoma status, because of ungradable or absent photographs. The distribution of selected fruit and vegetable items was examined in the total study population. In the analysis, consumption of individual items was categorized into frequency categories reflective of their different frequency distributions on the questionnaires filled out by participants. The number of participants consuming a certain item may not add up to the total study population because of incomplete responses for the item. For further details see reference .
Because it is presumably the constituents (eg, vitamins, minerals) of fruits and vegetables that confer a protective effect, the major nutrient components of fruits and vegetables were determined. The total intake of calories, fat, protein, and carbohydrate were also calculated based on the consumption of all food. The relationships of both food items and nutrients to the risk of glaucoma were examined individually using logistic regression models, adjusted for potential confounders. The potential confounders were chosen based on their clinical relevance and evidence from the literature, and are seen in Table 1 . Because of the skewed distribution of antioxidant intake, intakes were categorized into either tertiles or quartiles, depending on where easily recognized cut-offs were seen. The lowest tertile or quartile of intake formed the reference category. Trend P values were determined from the multiple logistic regression models of the odds of glaucoma adjusting for the potential confounders listed above. Trend P values indicate whether a dose-response effect exists when consuming a higher amount of food items or nutrients.
| Characteristics | All Women (N = 584) N (%) or Mean ± SD | Women With Glaucoma (N = 77) N (%) or Mean ± SD | Women Without Glaucoma (N = 507) N (%) or Mean ± SD | P Value |
|---|---|---|---|---|
| Study sites | .543 a | |||
| Baltimore | 137 (23.5%) | 15 (19.5%) | 122 (24.1%) | |
| Minneapolis | 146 (25.0%) | 18 (23.4%) | 128 (25.3%) | |
| Pittsburgh | 157 (26.9%) | 20 (26.0%) | 137 (27.0%) | |
| Portland | 144 (24.7%) | 24 (31.2%) | 120 (23.7%) | |
| Age (y) | ||||
| Mean ± SD | 75.3 ± 5.1 | 77.0 ± 5.5 | 75.1 ± 5.0 | .003 b |
| 65–74 | 295 (50.5%) | 30 (39.0%) | 265 (52.3%) | .065 a |
| 75–79 | 172 (29.5%) | 25 (32.5%) | 147 (29.0%) | |
| 80–84 | 84 (14.4%) | 14 (18.2%) | 70 (13.8%) | |
| 85–94 | 33 (5.7%) | 8 (10.4%) | 25 (4.9%) | |
| Education (y) | ||||
| Mean ± SD | 12.1 ± 3.2 | 12.1 ± 3.5 | 12.1 ± 3.1 | .939 b |
| <12 y | 192 (33.2%) | 23 (29.9%) | 169 (33.7%) | .675 a |
| 12 y | 187 (32.3%) | 24 (31.2%) | 163 (32.5%) | |
| >12 y | 200 (34.5%) | 30 (39.0%) | 170 (33.9%) | |
| Current smoker | 48 (8.3%) | 6 (7.9%) | 42 (8.3%) | 1.00 a |
| At least 1 alcoholic drink in past 30 d | 154 (26.4%) | 19 (24.7%) | 135 (26.7%) | .782 a |
| Walking for exercise | 212 (36.5%) | 19 (25.0%) | 193 (38.2%) | .030 a |
| Body mass index (kg/m 2 ) | ||||
| Mean ± SD | 30.2 ± 6.0 | 31.2 ± 6.2 | 30.0 ± 6.0 | .098 b |
| Self-rated health status | .414 a | |||
| Good or excellent | 419 (71.9%) | 52 (67.5%) | 367 (72.5%) | |
| Fair or poor | 164 (28.1%) | 25 (32.5%) | 139 (27.5%) | |
| Self-report of diabetes | 101 (17.3%) | 12 (15.6%) | 89 (17.6%) | .748 a |
| Self-report of hypertension | 370 (63.5%) | 43 (55.8%) | 327 (64.6%) | .162 a |
A power calculation was performed at the start of this study based on the results of previous analysis of 1155 Study of Osteoporotic Fractures participants that included only 144 African-American participants. Drawing on the results of that study, where some relationships appeared stronger in the African-American cohort, one of the key distinctions anticipated to occur was between subjects reporting less than 1 serving of spinach per week and those reporting at least 1 serving per week. With assumed alternate prevalence rates for glaucoma between 10% and 12% and intake of less than 1 serving per week or between prevalence rates of 2% and 3% with more than 1 serving per week, study power was calculated to lie between 95% and 99.9%, assuming at least 500 patients with gradable photos. All statistical analyses were performed using SAS version 9.1 statistical software (SAS institute, Cary, North Carolina, USA).
Results
Study Population
Among the 662 African-American women in the cohort, glaucoma status could not be determined in 68 women because of missing or ungradable disc photographs (10.3%; 47 with unknown status bilaterally and 21 with unknown status unilaterally with a normal fellow eye). Additionally, there were 13 women (1.9%) for whom we did not have Food Frequency Questionnaire data; 3 of them also had unknown glaucoma status. Thus, the final study population consisted of 584 women (88.2% of the original African-American cohort). There were no statistically significant differences in baseline characteristics among the 78 women excluded from analyses (data not shown).
The characteristics of the study population are described in Table 1 .
Prevalence of Glaucoma
Among the 584 women in the analysis, 77 (13.2%) were diagnosed with glaucoma in at least 1 eye. Glaucoma was bilateral in 32 women and unilateral in 39, and there were 6 women with glaucoma in 1 eye but unknown status in the fellow eye.
Relationship Between Fruit/Vegetable Intake and Glaucoma: Adjusted Analyses
Fruit and vegetable consumption varied among study participants, with a somewhat even spread across the various frequency categories ( Table 2 ). In analyses adjusted for potential confounders ( Table 2 ), the odds of having glaucoma were decreased by 79% (odds ratio [OR] = 0.21; 95% confidence interval [CI] = 0.08–0.60) in women who consumed 3 or more servings per day of all fruits and fruit juices compared to those who consumed less than 1 serving per day (trend P = .023). Compared to the reference group (<1 serving per day of fruit), those women consuming 2 servings per day and at least 1 serving per day had a 37% (OR = 0.63; 95% CI = 0.32–1.24) and 65% (OR = 0.35; 95% CI = 0.18–0.70) decreased odds of glaucoma, respectively. Of the individual fruits analyzed, women consuming greater amounts of fresh oranges (OR = 0.18; CI = 0.06–0.51; P = .002) and fresh peaches (OR = 0.30; CI = 0.13–0.67; P = .002) were 82% and 70% less likely to have glaucoma, respectively. The frequencies compared for these fruits were more than 2 servings per week compared to less than 1 serving per week. Consumption of apples/applesauce, bananas, orange juice, or canned/dried peaches did not show any statistically significant benefits or harms with relation to glaucoma and there were no significant trends with higher consumption.
| Average Intake of Fruits/Vegetables | N (%) | OR (95% CI) a |
|---|---|---|
| All fruits and fruit juices | ||
| <1 serving per day | 121(21%) | 1.00 (referent) |
| 1 serving per day | 216 (37%) | 0.35 (0.18–0.70) |
| 2 servings per day | 157 (27%) | 0.63 (0.32–1.24) |
| ≥3 servings per day | 90 (15%) | 0.21 (0.08–0.60) |
| Trend P value | .023 | |
| All vegetables | ||
| <1 serving per day | 62 (11%) | 1.00 (referent) |
| 1 serving per day | 202 (35%) | 0.95 (0.39–2.28) |
| 2 servings per day | 178 (30%) | 1.02 (0.41–2.53) |
| ≥3 servings per day | 142 (24%) | 0.97 (0.37–2.54) |
| Trend P value | .965 | |
| Fresh apple | ||
| <1 serving per week | 171 (34%) | 1.00 (referent) |
| 1 serving per week | 57 (11%) | 0.32 (0.10–1.02) |
| 2 servings per week | 99 (20%) | 0.84 (0.40–1.77) |
| >2 servings per week | 171 (34%) | 0.52 (0.26–1.05) |
| Trend P value | .137 | |
| Fresh banana | ||
| <1 serving per week | 95 (17%) | 1.00 (referent) |
| 1–2 servings per week | 117 (21%) | 0.73 (0.31–1.75) |
| 3–6 servings per week | 228 (41%) | 1.02 (0.48–2.15) |
| ≥1 serving per day | 112 (20%) | 1.05 (0.44–2.48) |
| Trend P value | .661 | |
| Fresh orange | ||
| <1 serving per week | 153 (39%) | 1.00 (referent) |
| 1 serving per week | 42 (11%) | 0.83 (0.28–2.48) |
| 2 servings per week | 85 (22%) | 0.70 (0.30–1.61) |
| >2 servings per week | 111 (28%) | 0.18 (0.06–0.51) |
| Trend P value | .002 | |
| Orange juice | ||
| ≤1 serving per week | 191 (33%) | 1.00 (referent) |
| 3 servings per week to <1 serving per day | 185 (32%) | 0.77 (0.41–1.44) |
| ≥1 serving per day | 205 (35%) | 0.79 (0.42–1.47) |
| Trend P value | .448 | |
| Fresh peach | ||
| <1 serving per week | 156 (36%) | 1.00 (referent) |
| 1 serving per week | 60 (14%) | 0.86 (0.38–1.98) |
| 2 servings per week | 84 (19%) | 0.42 (0.17–1.02) |
| >2 servings per week | 134 (31%) | 0.30 (0.13–0.67) |
| Trend P value | .002 | |
| Canned/dried peach | ||
| <1 serving per month | 239 (41%) | 1.00 (referent) |
| 1 serving per month to <1 serving per week | 183 (32%) | 1.07 (0.60–1.91) |
| ≥1 serving per week | 157 (27%) | 0.65 (0.33–1.28) |
| Trend P value | .258 | |
| Fresh carrot | ||
| ≤1 serving per month | 85 (16%) | 1.00 (referent) |
| >1 serving per month to <1 serving per week | 136 (26%) | 1.23 (0.54–2.83) |
| 1 serving per week | 105 (20%) | 0.81 (0.32–2.05) |
| >1 serving per week | 190 (37%) | 0.57 (0.24–1.34) |
| Trend P value | .061 | |
| Spinach (cooked or raw) | ||
| ≤1 serving per month | 129 (29%) | 1.00 (referent) |
| >1 serving per month to <1 serving per week | 125 (28%) | 1.19 (0.57–2.46) |
| 1 serving per week | 96 (22%) | 0.62 (0.26–1.45) |
| >1 serving per week | 96 (22%) | 0.54 (0.22–1.35) |
| Trend P value | .094 | |
| Green salad | ||
| <1 serving per week | 141 (27%) | 1.00 (referent) |
| 1 serving per week | 86 (17%) | 1.43 (0.62–3.30) |
| 2 servings per week | 84 (16%) | 1.28 (0.52–3.14) |
| >2 servings per week | 210 (40%) | 1.02 (0.48–2.17) |
| Trend P value | .909 | |
| Green collards/kale | ||
| ≤1 serving per month | 178 (30%) | 1.00 (referent) |
| >1 serving per month to <1 serving per week | 162 (28%) | 0.45 (0.24–0.88) |
| 1 serving per week | 85 (15%) | 0.48 (0.22–1.09) |
| >1 serving per week | 159 (27%) | 0.43 (0.21–0.85) |
| Trend P value | .014 |
a Based on multiple logistic regression models of the odds of glaucoma adjusting for potential confounders including study sites, age, education, smoking status, alcohol consumption, walking for exercise, body mass index, self-rated health status, presence of self-reported diabetes, and presence of self-reported hypertension.
The odds of having glaucoma were not affected by consumption of 3 or more servings of vegetables per day compared to less than 1 serving (OR = 0.97; CI = 0.37–2.54; trend P = .965). However, consumption of more than 1 serving per week of green collards/kale decreased the odds of having glaucoma by 57% (OR = 0.43; CI = 0.21–0.85) compared to consuming less than 1 serving per month (trend P = .014). Eating greater amounts of spinach and fresh carrots came close to showing a statistically significant protective trend (trend P = .094 and P = .061, respectively). Higher green salad consumption showed no protective or harmful trend.
Relationship Between Individual Nutrient Intake and Glaucoma
After adjusting for potential confounders, the highest quartiles or tertiles of intake of the following nutrients were associated with decreased odds of having glaucoma: vitamin C 70% less likely (trend P = .018), vitamin A 63% less likely (trend P = .011), and α-carotene 54% less likely ( P = .021) ( Table 3 ). The trend results for higher dietary intake of β-carotene (trend P = .052), folate (trend P = .056), and lutein/zeaxanthin (trend P = .077) were very close to being statistically significant. Higher intake levels of vitamins B1, B2, B3, B6, D, E, lycopene, and potassium were not associated with statistically significant increased or decreased odds of having glaucoma. Intake of increasing calories per day, total carbohydrate, total protein ( Table 3 ), and total fat ( Table 4 ) also showed no trend or effect on the odds of glaucoma.
| Average Daily Intake of Nutrients From Food | N (%) | OR (95% CI) a |
|---|---|---|
| Vitamin A (RE) | ||
| <800 | 155 (27%) | 1.00 (referent) |
| 800–1099 | 135 (23%) | 1.35 (0.69–2.65) |
| 1100–1499 | 146 (25%) | 0.93 (0.47–1.86) |
| ≥1500 | 148 (25%) | 0.37 (0.15–0.90) |
| Trend P value | .011 | |
| Vitamin B (folate) (μg) | ||
| <180 | 163 (28%) | 1.00 (referent) |
| 180–229 | 136 (23%) | 0.61 (0.30–1.22) |
| 230–299 | 128 (22%) | 0.70 (0.35–1.40) |
| ≥300 | 157 (27%) | 0.47 (0.22–0.96) |
| Trend P value | .056 | |
| Vitamin B1 (thiamin) (mg) | ||
| <1 | 238 (41%) | 1.00 (referent) |
| 1–1.4 | 243 (42%) | 0.65 (0.37–1.14) |
| ≥1.5 | 103 (18%) | 0.84 (0.41–1.72) |
| Trend P value | .455 | |
| Vitamin B2 (riboflavin) (mg) | ||
| <1 | 129 (22%) | 1.00 (referent) |
| 1–1.3 | 160 (27%) | 0.77 (0.38–1.57) |
| 1.4–1.8 | 162 (28%) | 0.73 (0.35–1.50) |
| ≥1.9 | 133 (23%) | 0.75 (0.35–1.62) |
| Trend P value | .529 | |
| Vitamin B3 (niacin) (mg) | ||
| <11 | 135 (23%) | 1.00 (referent) |
| 11–14 | 166 (28%) | 0.71 (0.36–1.40) |
| 15–18 | 153 (26%) | 0.61 (0.29–1.26) |
| ≥19 | 130 (22%) | 0.64 (0.30–1.38) |
| Trend P value | .251 | |
| Vitamin B6 (mg) | ||
| <1.1 | 152 (26%) | 1.00 (referent) |
| 1.1–1.3 | 159 (27%) | 0.72 (0.37–1.43) |
| 1.4–1.6 | 112 (19%) | 0.88 (0.43–1.83) |
| ≥1.7 | 161 (28%) | 0.65 (0.32–1.32) |
| Trend P value | .299 | |
| Vitamin C (mg) | ||
| <60 | 128 (22%) | 1.00 (referent) |
| 60–99 | 179 (31%) | 0.37 (0.18–0.76) |
| 100–139 | 147 (25%) | 0.58 (0.29–1.14) |
| ≥140 | 130 (22%) | 0.30 (0.13–0.70) |
| Trend P value | .018 | |
| Vitamin D (IU) | ||
| <70 | 138 (24%) | 1.00 (referent) |
| 70–119 | 153 (26%) | 0.76 (0.38–1.53) |
| 120–179 | 151 (26%) | 0.61 (0.29–1.30) |
| ≥180 | 142 (24%) | 0.91 (0.45–1.83) |
| Trend P value | .915 | |
| Vitamin E (A-TE) | ||
| <5 | 135 (23%) | 1.00 (referent) |
| 5–6.9 | 163 (28%) | 1.22 (0.61–2.44) |
| 7–8.9 | 140 (24%) | 1.00 (0.47–2.12) |
| ≥9 | 146 (25%) | 0.76 (0.35–1.66) |
| Trend P value | .327 | |
| Alpha-carotene (μg) | ||
| <200 | 226 (39%) | 1.00 (referent) |
| 200–399 | 176 (30%) | 0.69 (0.38–1.26) |
| ≥400 | 182 (31%) | 0.45 (0.23–0.88) |
| Trend P value | .021 | |
| Beta-carotene (μg) | ||
| <2000 | 157 (27%) | 1.00 (referent) |
| 2000–3199 | 144 (25%) | 0.61 (0.31–1.20) |
| 3200–4799 | 137 (23%) | 0.54 (0.27–1.11) |
| ≥4800 | 146 (25%) | 0.46 (0.22–0.95) |
| Trend P value | .052 | |
| Cryptoxanthin (μg) | ||
| <60 | 163 (28%) | 1.00 (referent) |
| 60–99 | 134 (23%) | 1.26 (0.63–2.51) |
| 100–149 | 157 (27%) | 0.98 (0.50–1.94) |
| ≥150 | 130 (22%) | 0.62 (0.28–1.36) |
| Trend P value | .171 | |
| Lutein/zeaxanthin (μg) | ||
| <1400 | 152 (26%) | 1.00 (referent) |
| 1400–2199 | 130 (22%) | 0.44 (0.21–0.90) |
| 2200–3999 | 160 (27%) | 0.42 (0.21–0.84) |
| ≥4000 | 142 (24%) | 0.43 (0.21–0.88) |
| Trend P value | .077 | |
| Lycopene (μg) | ||
| <400 | 158 (27%) | 1.00 (referent) |
| 400–799 | 150 (26%) | 0.70 (0.35–1.43) |
| 800–1199 | 124 (21%) | 0.69 (0.32–1.48) |
| ≥1200 | 152 (26%) | 0.94 (0.47–1.87) |
| Trend P value | .917 | |
| Potassium (mg) | ||
| <1700 | 154 (26%) | 1.00 (referent) |
| 1700–2099 | 132 (23%) | 0.75 (0.36–1.55) |
| 2100–2699 | 146 (25%) | 0.70 (0.34–1.44) |
| ≥2700 | 152 (26%) | 0.83 (0.41–1.70) |
| Trend P value | .670 | |
| Total calories (Kcal) | ||
| <1100 | 172 (29%) | 1.00 (referent) |
| 1100–1399 | 133 (23%) | 0.72 (0.35–1.51) |
| 1400–1799 | 161 (28%) | 0.87 (0.44–1.71) |
| ≥1800 | 118 (20%) | 1.06 (0.51–2.18) |
| Trend P value | .786 | |
| Total protein (g) | ||
| <40 | 130 (22%) | 1.00 (referent) |
| 40–54 | 157 (27%) | 0.47 (0.22–0.99) |
| 55–69 | 142 (24%) | 0.77 (0.38–1.58) |
| ≥70 | 155 (27%) | 0.65 (0.32–1.34) |
| Trend P value | .460 | |
| Total carbohydrate (g) | ||
| <120 | 126 (22%) | 1.00 (referent) |
| 120–159 | 167 (29%) | 0.69 (0.34–1.40) |
| 160–209 | 154 (26%) | 0.72 (0.35–1.48) |
| ≥210 | 137 (23%) | 0.75 (0.35–1.59) |
| Trend P value | .613 |
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