Abstract
While both the 2012 and 2014 Consumer Reports concerned arsenic levels in US rice, no previous study has evaluated long-term consumption of total rice, white rice and brown rice in relation to risk of developing cancers. We investigated this in the female Nurses' Health Study (1984-2010), and Nurses' Health Study II (1989-2009), and the male Health Professionals Follow-up Study (1986-2008), which included a total of 45,231 men and 160,408 women, free of cancer at baseline. Validated food frequency questionnaires were used to measure rice consumption at baseline and repeated almost every 4 years thereafter. We employed Cox proportional hazards regression model to estimate multivariable relative risks (RRs) and 95% confidence intervals (95% CIs). During up to 26 years of follow-up, we documented 31,655 incident cancer cases (10,833 in men and 20,822 in women). Age-adjusted results were similar to multivariable-adjusted results. Compared to participants with less than one serving per week, the multivariable RRs of overall cancer for individuals who ate at least 5 servings per week were 0.97 for total rice (95% CI: 0.85-1.07), 0.87 for white rice (95% CI: 0.75-1.01), and 1.17 for brown rice (95% CI: 0.90-1.26). Similar non-significant associations were observed for specific sites of cancers including prostate, breast, colon and rectum, melanoma, bladder, kidney, and lung. Additionally, the null associations were observed among European Americans and non-smokers, and were not modified by BMI. Long-term consumption of total rice, white rice or brown rice was not associated with risk of developing cancer in US men and women.
Keywords: rice, arsenic, prostate cancer, breast cancer, colorectal cancer, melanoma, bladder cancer, kidney cancer, lung cancer
Introduction
Paddy rice is a major component of the global food supply, serving as a staple for over 50% of the world population 1. Compared to Asian countries, per capita rice consumption in the US is much lower with substantial variation across ethnic groups2. White rice, as milled grain with husk, bran and germ removed, has a finer texture and longer shelf life. In contrast, brown rice is a whole grain, produced by only removing the outermost layer (husk) and thus contains more dietary fiber, minerals, and biologically active substances3-6.
Both the 2012 and 2014 Consumer Reports claimed that “samples of white rice, brown rice and rice breakfast cereals that many U.S. adults and children eat may contain worrisome levels of arsenic”7. While arsenic is a naturally occurring element found in air, soil, water, and foods, inorganic arsenic has been linked with various types of cancers, including those of the lung, liver, bladder, kidney and skin8-12. Nonetheless, it remains unclear whether arsenic intakes at the levels found in rice are related to risk of human cancer.
Hence, we conducted this first study to comprehensively evaluate whether individuals with relatively high amounts of rice consumption over decades have a higher risk of developing cancers. Specifically, we utilized unique data from three well-established on-going prospective cohorts, the female Nurses’ Health Study and Nurses’ Health Study II, and the male Health Professionals Follow-up Study. In each cohort we have collected detailed information on consumption of white rice and brown rice every 4 years for up to 26 years.
Materials and Methods
Study population
We used the data from three on-going prospective US cohorts: the Nurses' Health Study (NHS, n = 121,700 registered female nurses, aged 30 to 55 years at baseline in 1976), the Nurses’ Health Study II (NHS II, n = 116,609 registered female nurses, aged 25 to 42 at baseline in 1989), and the Health Professionals Follow-up Study (HPFS, n = 51,529 male professionals, aged 40 to 75 years at baseline in 1986). Details of these three cohorts have been described elsewhere 13-15. In all three cohorts, participants at enrollment completed baseline questionnaires regarding lifestyle, diet and newly diagnosed diseases. During the follow-up questionnaires were administered every 2 years to update medical, lifestyle and other health-related information. The follow-up rate has been greater than 90% for each cohort.
In the current analysis, we excluded participants with diagnosis of cancer at baseline and those with missing date of cancer diagnosis. In addition, we excluded participants with missing information on rice consumption at baseline, those with unusual self-reported total energy intake (i.e. < 500 or > 3500 kcal/day for NHS and NHS II; < 800 or > 4200 kcal/day for HPFS). After exclusion, data from 70,144 (of 81,755) NHS participants, 90,264 (of 95,452) NHS II participants, and 45,231 (of 51,530) HPFS participants were available for the analysis.
These cohorts have been approved by the institutional review boards at the Harvard School of Pubic Heath and Brigham and Women’s Hospital, Boston, Massachusetts. The completion of the self-administered questionnaire was considered to imply informed consent..
Assessment of rice consumption
Information on rice consumption was first assessed in 1980 in NHS participants using a validated semi-quantitative food frequency questionnaire (SFFQ), and repeated in 1984, 1986, and every 4 years thereafter. Similar SFFQs were administered every 4 years for NHS II participants during 1991 through 2009 and for HPFS participants during 1986 through 2008. In each SFFQ, we asked the participants how often, on average over the past year, they consumed a specified portion size of each food, with nine possible frequency choices ranging from “almost never” to “6 or more times per day”. For white rice and brown rice, we used 1 cup as the serving unit. The total rice intake was calculated as the sum of white rice and brown rice. In the current study, we categorized participants’ rice intake into 4 categories (< 1 serving per week, 1 serving per week, 2-4 servings per week and ≥ 5 servings per week). The reproducibility and validity of these SFFQs have been evaluated in detail elsewhere16-19. Assessments of white rice and brown rice consumption were moderately correlated with diet record assessments. For example, the corrected Pearson correlation coefficients between these 2 assessments were 0.53 for white rice and 0.41 for brown rice in the HPFS 16.
Assessment of other covariates
Other dietary factors such as consumption of red meat, fish, alcohol, fruit and vegetables, whole grain, nuts were also collected from the baseline and subsequent SFFQs. Nutrient intakes were calculated as the frequency of intake multiplied by the nutrient composition of the specified portion size; the composition values were obtained mainly from U.S. Department of Agriculture sources, supplemented with other data. In addition, we also collected and updated information on medical, lifestyle and other health-related factors, such as body weight, physical activity, smoking status, family history of cancer, multivitamin use, and history of diabetes, hypertension and hypercholesterolemia. In NHS and NHS II, we also queried postmenopausal hormone use.
Ascertainment of incident cancer cases
In each cohort, participants reported cancer and other disease endpoints in biennial questionnaires. Researchers obtained permission from the study participants to obtain their medical records and pathological reports and abstracted the information on anatomic location, stage, and histological type of the cancer. The confirmed cancers were defined according to the International Classification of Diseases, Ninth Revision [ICD-9]20.
Statistical analysis
We computed person-time of follow-up for each participant from the return date of the baseline questionnaire to the date of cancer diagnosis, death from any cause, or the end of follow-up (May 31st, 2010 in NHS, May 31st, 2009 in NHS II, and January 31st, 2008 in HPFS), whichever came first. Relative risks (RRs) and 95% confidence intervals (CI’s) of total and site-specific cancers were estimated using time-dependent Cox proportional hazards regression models 21. All models were stratified by age in months and calendar time. In multivariate analysis, we simultaneously controlled for ethnicity and other factors that may influence cancer risk (see Table 2 footnote for these variables and their categorizations). In NHS and NHS II, we further adjusted for postmenopausal hormone use (never, past, current). To better represent long-term diet and minimize the effect of within-person variation, we used the cumulative average intake method 22. Specifically we calculated the cumulative average from all SFFQs until the diagnosis of cancer, death, or the end of follow-up. To address the missing dietary information in repeated SFFQs, we replaced the missing values of dietary variables with those from the previous SFFQ.
Table 2.
Risk of Overall Cancer According to Total Rice Intake in the HPFS, NHS I, nad NHS II
| White Rice Intake, No. of Servings | |||||
|---|---|---|---|---|---|
| < 1/week | 1/week | 2-4/week | ≥ 5/week | p-value | |
| NHS | |||||
| No. of cases | 6,931 | 3,442 | 4,776 | 524 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 1.00 (0.96, 1.04) | 0.98 (0.94, 1.01) | 0.94 (0.86, 1.02) | 0.08 |
| Model 2b | 1 (ref) | 1.01 (0.97, 1.05) | 1.00 (0.96, 1.04) | 1.02 (0.93, 1.12) | 0.81 |
| Model 3c | 1 (ref) | 1.01 (0.97, 1.05) | 1.00 (0.96, 1.04) | 1.02 (0.93, 1.12) | 0.72 |
|
| |||||
| NHS II | |||||
| No. of cases | 1,693 | 1,165 | 1,904 | 387 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 0.94 (0.87, 1.01) | 0.95 (0.89, 1.02) | 0.82 (0.73, 0.92) | 0.001 |
| Model 2b | 1 (ref) | 0.92 (0.86, 1.00) | 0.92 (0.86, 0.98) | 0.82 (0.73, 0.92) | 0.001 |
| Model 3c | 1 (ref) | 0.93 (0.86, 1.00) | 0.93 (0.86, 0.99) | 0.83 (0.73, 0.94) | 0.003 |
|
| |||||
| HPFS | |||||
| No. of cases | 3,920 | 2,290 | 3,751 | 872 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 0.98 (0.93, 1.03) | 0.99 (0.95, 1.04) | 0.94 (0.87, 1.01) | 0.14 |
| Model 2b | 1 (ref) | 0.99 (0.94, 1.04) | 1.00 (0.95, 1.04) | 1.00 (0.92, 1.08) | 0.99 |
| Model 3c | 1 (ref) | 0.99 (0.94, 1.04) | 1.00 (0.95, 1.05) | 1.00 (0.93, 1.10) | 0.85 |
|
| |||||
| Pooled results | |||||
| RR (95% CI) | 1 (ref) | 0.98 (0.93, 1.03) | 0.98 (0.94, 1.02) | 0.97 (0.85, 1.07) | 0.37 |
| P heterogeneity | 0.07 | 0.10 | 0.02 | 0.02 | |
Abbreviation: C I, confidence interval; HPFS, Health Professionals Follow-up Study; NHS, Nurses’ Health Study
Age-adjusted.
Adjusted for age (years), ethnicity (European Americans, Asian, African American, other), body mass index (calculated as weight in kilograms divided by height in meters squared; <21.0, 21.0-22,9, 23.0-24.9, 25.0.26.9, 27.0-29.9, 30.0-32.9, or ≥ 35.0) smoking status (never smoked, past smokers, current smokers 1-14 cigarettes/day, 15-24 cigarettes/day, or ≥ 25 cigarettes/day), physical activity (MET-hours/week, in quintiles), family history of cancer (yes or no), multivitamin supplementation (yes or no), and total energy intake (kilocalories/day, in quintiles). For women, postmenopausal hormone use (yes or no) was further adjusted for.
In addition to model 2, model 3 was further adjusted for intake of alcohol, fruit, vegetables, red meat, fish, nuts, whole grain (except brown rice), sugar-sweetened beverage (all in quartiles).
In addition to overall cancer, we further investigated the risk of common site-specific cancers, including prostate cancer, breast cancer, lung cancer, colorectal cancer, bladder cancer, kidney cancer and melanoma. In NHS II, only breast cancer and melanoma were included in the site-specific analysis due to the small number of cases for other cancers. We also conducted several sensitivity analyses: (1) for total rice consumption, we examined intake of at least 1 serving/day; (2) in men, we also excluded the cases of organ-confined prostate cancer, as those were usually detected from PSA screening test and had high incidence but good prognosis; (3) we applied 4 to 8 years lag due to concern of reverse causation because participants with subclinical malignancy may change their diet due to the illness; (4) we further examined whether the associations were modified by ethnicity, smoking status, and body mass index (BMI). In our 3 cohorts, the majority of participants are European Americans, and we were unable to have stable estimate in other ethnicity due to small sample size. Therefore, we restricted the stratified analysis to European Americans . Similarly we conducted analyses stratified by smoking status (never, past, and current) and by BMI (< 25, 25-30, and ≥ 30 kg/m2).
Tests for trend were conducted by assigning the median value to each category and using this variable as a continuous variable in the models. We used the meta-analysis assuming fixed-effects to pool the RRs from multivariate models across the 3 cohorts. P values for heterogeneity between cohorts were calculated by Cochran Q test 23. All P values were 2-sided and all statistical procedures were performed using SAS release 9.2 (SAS Institute, Cary, NC)
Results
We identified 15,673 incident cancer cases during 26 years of follow-up in the NHS, 5,149 cases during 18 years in the NHS II, and 10,833 cases during 22 years in the HPFS. In NHS, breast cancer was the most common cancer (n = 5,714; 36.8%), followed by colorectal cancer (n = 1,352; 8.7%) and lung cancer (n = 1,205; 7.7%). In NHS II, breast cancer was the most common cancer (n = 2,401; 47.0%) and melanoma was the next common cancer (n = 538; 10.4%). In HPFS, prostate cancer was the most common cancer (n = 5,060; 46.7%), followed by colorectal cancer (n = 1,042; 9.6%) and lung cancer (n = 742; 6.8%).
Baseline characteristics of the study participants according to the intake of white rice and brown rice are shown in table 1. In men and women, Asian participants were more likely to have higher white rice intake. Ethnicity was not strongly associated with brown rice intake. However, higher brown rice consumption in general was expectedly associated with more health-conscious diet and lifestyles variables, including greater level of physical activity, less cigarette smoking, more use of multivitamin supplement, and higher intake of fruit, vegetables and whole grain.
Table 1.
Baseline Age-Standardized Characteristics According to White Rice and Brown Rice Intake
| White Rice Intake | Brown Rice Intake | |||||||
|---|---|---|---|---|---|---|---|---|
| < 1/wk | 1/wk | 2-4/wk | ≥ 5/wk | < 1/wk | 1/wk | 2-4/wk | ≥ 5/wk | |
| NHS | ||||||||
| Participants, No. | 47,461 | 5,126 | 640 | 4,461 | 1,291 | 198 | ||
| Age, y | 50.8 | 49.5 | 49.5 | 50.2 | 50.3 | 50.5 | 51.1 | 51.6 |
| Rice intake, servings/d | 0.047 | 0.14 | 0.43 | 1.04 | 0.013 | 0.14 | 0.43 | 0.99 |
| Physical activity, MET-h/wk | 13.8 | 14.2 | 15.1 | 15.7 | 13.5 | 19.0 | 22.1 | |
| BMI, km2 | 25.1 | 25.0 | 24.9 | 24.4 | 25.1 | 24.6 | 24.3 | 23.7 |
| Race, % | ||||||||
| European Americans | 98.8 | .1 | 93.7 | 50.9 | 97.9 | 98.1 | 96.4 | 92.6 |
| Asian | 0.16 | 0.25 | 1.6 | 41.9 | 0.7 | 0.3 | 1.0 | 2.6 |
| African-American | 0.33 | 0.62 | 1.6 | 1.6 | 1.0 | 0.9 | 1.9 | 2.5 |
| Other | 0.72 | 1.08 | 3.1 | 5.7 | 0.5 | 0.7 | 0.8 | 2.3 |
| Never smoking, % | 43.9 | 43.1 | 44.5 | 56.3 | 43.8 | 43.6 | 45.2 | 53.4 |
| Type 2 diabetes, % | 3.2 | 3.1 | 3.3 | 4.9 | 3.2 | 2.9 | 3.0 | 3.6 |
| Current multivitamin use, % | 36.9 | 36.2 | 37.4 | 37.2 | 35.8 | 46.3 | 52.2 | 48.1 |
| Dietary intake | ||||||||
| Alcohol, g/d | 6.5 | 7.5 | 8.1 | 3.9 | 6.8 | 7.5 | 6.8 | 5.1 |
| Fruit, servings/d | 2.0 | 2.2 | 2.3 | 2.5 | 2.1 | 2.6 | 2.9 | 3.0 |
| Vegetables, servings/d | 2.4 | 2.7 | 3.0 | 2.9 | 2.4 | 3.1 | 3.5 | 4.0 |
| Red meat, servings/d | 1.2 | 1.3 | 1.3 | 1.4 | 1.3 | 1.1 | 1.0 | 0.7 |
| Fish, servings/d | 0.2 | 0.2 | 0.3 | 0.3 | 0.2 | 0.3 | 0.3 | 0.3 |
| Whole grain, g/d | 14.4 | 13.3 | 13.1 | 10.4 | 12.9 | 22.2 | 37.0 | 66.7 |
|
| ||||||||
| NHS II | ||||||||
| Participants, No. | 50,134 | 26,436 | 11,727 | 1,967 | 74,030 | 11,406 | 4,201 | 627 |
| Age, y | 35.9 | 36.3 | 36.4 | 36.3 | 36.1 | 36 | 36.2 | 36.6 |
| Rice intake, servings/d | 0.045 | 0.14 | 0.43 | 1.14 | 0.019 | 0.14 | 0.43 | 0.93 |
| Physical activity, MET-h/wk | 20.6 | 20.6 | 22.1 | 21.3 | 19.4 | 26 | 28.9 | 38.6 |
| BMI, kg/m2 | 24.7 | 24.6 | 24.6 | 24 | 24.7 | 24.1 | 24.0 | 24.0 |
| Race, % | ||||||||
| European Americans | 94.5 | 94.1 | 89.2 | 50.9 | 92.5 | 94.6 | 92.8 | 85.8 |
| Asian | 0.4 | 0.8 | 2.5 | 37.0 | 1.7 | 0.8 | 0.9 | 4.2 |
| African-American | 1.2 | 1.3 | 2.5 | 4.1 | 1.6 | 0.9 | 1.2 | 4.0 |
| Other | 3.9 | 3.9 | 5.8 | 8.0 | 4.2 | 3.7 | 5.1 | 6.0 |
| Never smoking, % | 65.7 | 65.3 | 65.1 | 74.5 | 66.2 | 63.9 | 61.5 | 61.6 |
| Type 2 diabetes, % | 1.0 | 1.0 | 0.9 | 1.0 | 1.0 | 0.8 | 0.9 | 1.2 |
| Current multivitamin use, % | 43.8 | 43.3 | 44.9 | 43.7 | 42.5 | 48.9 | 51.0 | 52.5 |
| Dietary intake | ||||||||
| Alcohol, g/d | 2.9 | 3.3 | 3.5 | 2.4 | 3.0 | 3.7 | 3.8 | 3.1 |
| Fruit, servings/d | 1.1 | 1.3 | 1.4 | 1.4 | 1.1 | 1.5 | 1.7 | 2.0 |
| Vegetables, servings/d | 3.0 | 3.5 | 4.0 | 4.3 | 3.1 | 4.0 | 4.8 | 6.1 |
| Red meat, servings/d | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 | 0.7 | 0.6 | 0.5 |
| Fish, servings/d | 0.2 | 0.3 | 0.3 | 0.4 | 0.3 | 0.3 | 0.4 | 0.4 |
| Whole grain, g/d | 20.8 | 20.1 | 20.2 | 16.4 | 17.7 | 27.3 | 43.4 | 66.8 |
|
| ||||||||
| HPFS | ||||||||
| Participants, No. | 28,432 | 11,295 | 4,748 | 907 | 36,917 | 5,966 | 2,131 | 368 |
| Age, y | 54.6 | 52.2 | 52.1 | 51.7 | 54.1 | 51.7 | 52.3 | 52.5 |
| Rice intake, servings/d | 0.04 | 0.14 | 0.43 | 1.06 | 0.02 | 0.41 | 0.43 | 0.98 |
| Physical activity, MET-h/wk | 20.8 | 21.6 | 21.0 | 20.3 | 20.0 | 24.4 | 26.8 | 33.3 |
| BMI, kg/m2 | 25.0 | 25.0 | 24.8 | 24.2 | 25.0 | 24.8 | 24.5 | 23.7 |
| Race, % | ||||||||
| European Americans | 96.7 | 96.0 | 91.0 | 48.5 | 95.0 | 96.1 | 94.3 | 83.4 |
| Asian | 0.3 | 0.5 | 3.9 | 46.1 | 1.7 | 0.6 | 1.6 | 12.9 |
| African-American | 0.7 | 1.0 | 2.6 | 2.2 | 1.0 | 0.9 | 1.6 | 1.1 |
| Other | 2.2 | 2.5 | 2.5 | 3.2 | 2.3 | 2.4 | 2.5 | 2.6 |
| Never smoking, % | 44.7 | 45.6 | 43.9 | 45.0 | 44.1 | 47.9 | 48.8 | 49.2 |
|
| ||||||||
| Type 2 diabetes, % | 3.0 | 3.2 | 3.4 | 4.3 | 3.1 | 3.1 | 3.2 | 2.8 |
| Current multivitamin use, % | 42.3 | 40.3 | 40.5 | 45.2 | 40.4 | 45.6 | 50.4 | 52.2 |
| Dietary intake | ||||||||
| Alcohol, g/d | 11.3 | 11.6 | 11.5 | 8.4 | 11.3 | 11.5 | 11.0 | 8.3 |
| Fruit, servings/d | 2.3 | 2.5 | 2.6 | 2.5 | 2.2 | 2.8 | 3.1 | 3.6 |
| Vegetables, servings/d | 2.9 | 3.3 | 3.7 | 3.4 | 2.9 | 3.7 | 4.3 | 5.1 |
| Red meat, servings/d | 1.1 | 1.2 | 1.2 | 1.2 | 1.2 | 1.0 | 0.9 | 0.5 |
| Fish, servings/d | 0.3 | 0.4 | 0.4 | 0.4 | 0.3 | 0.4 | 0.5 | 0.6 |
| Whole grain, g/d | 22.3 | 21.8 | 21.9 | 18.2 | 19.1 | 28.5 | 45.2 | 76.9 |
Values are means or percentages and are standardized to the age distribution of the study population except for the age variable; MET-h hours of metabolic equivalent tasks; BMI = body mass index.
As shown in Table 2, long-term total rice intake was not associated with risk of overall cancer incidence. Specifically, participants who ate at least 5 servings of total rice per week had a relative risk of 0.97 (95% CI 0.85-1.07; P for trend 0.37). Similarly, neither white rice intake (Table 3) nor brown rice intake (Table 4) was associated with overall cancer risk. For the same comparison, the multivariable RRs of overall cancer risk were 0.87 for white rice (95% CI 0.75-1.01; P for trend 0.17) and 1.07 for brown rice (95% CI 0.90-1.26; P for trend 0.97).
Table 3.
Risk of Overall Cancer According to White Rice Intake in the HPFS, NHS I, and NHS II
| White Rice Intake, No. of Servings | |||||
|---|---|---|---|---|---|
| < 1/week | 1/week | 2-4/week | ≥ 5/week | p-value | |
| NHS | |||||
| No. of cases | 9,588 | 3,093 | 2,815 | 177 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 1.00 (0.96, 1.05) | 1.01 (0.96, 1.05) | 0.85 (0.74, 0.99) | 0.20 |
| Model 2b | 1 (ref) | 1.01 (0.97, 1.05) | 1.02 (0.98, 1.06) | 0.96 (0.81, 1.14) | 0.74 |
| Model 3c | 1 (ref) | 1.01 (0.96, 1.05) | 1.02 (0.97, 1.06) | 0.96 (0.81, 1.14) | 0.80 |
|
| |||||
| NHS II | |||||
| No. of cases | 2,636 | 1,210 | 1,196 | 107 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 0.96 (0.90, 1.03) | 0.98 (0.92, 1.05) | 0.70 (0.58, 0.85) | 0.002 |
| Model 2b | 1 (ref) | 0.96 (0.89, 1.02) | 0.96 (0.89, 1.02) | 0.72 (0.58, 0.89) | 0.004 |
| Model 3c | 1 (ref) | 0.96 (0.89, 1.03) | 0.96 (0.90, 1.03) | 0.73 (0.59, 0.90) | 0.01 |
|
| |||||
| HPFS | |||||
| No. of cases | 6,391 | 2,102 | 2,087 | 253 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 1.01 (0.96, 1.06) | 1.03 (0.98, 1.08) | 0.84 (0.74, 0.95) | 0.09 |
| Model 2b | 1 (ref) | 1.02 (0.97, 1.07) | 1.03 (0.98, 1.08) | 0.92 (0.79, 1.06) | 0.76 |
| Model 3c | 1 (ref) | 1.02 (0.97, 1.07) | 1.03 (0.98, 1.08) | 0.91 (0.79, 1.05) | 0.70 |
|
| |||||
| Pooled results | |||||
| RR (95% CI) | 1 (ref) | 1.00 (0.97, 1.03) | 1.01 (0.97, 1.04) | 0.87 (0.75, 1.01) | 0.17 |
| P heterogeneity | 0.32 | 0.24 | 0.28 | 0.07 | |
Abbreviation: CI, confidence interval; HPFS, Health Professionals Follow-up Study; NHS, Nurses’ Health Study
Age-adjusted.
Adjusted for the same sets of covariates as for model 2 and model 3 in table 2
Adjusted for the same sets of covariates as for model 2 and model 3 in table 2
Table 4.
Risk of Overall Cance According to Brown Rice Intake in the HPFS, NHS I, and NHS II
| Brown Rice Intake, No. of Servings | |||||
|---|---|---|---|---|---|
| < 1/week | 1/week | 2-4/week | ≥ 5/week | p-value | |
| NHS | |||||
| No. of cases | 14,107 | 798 | 707 | 61 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 0.99 (0.92, 1.06) | 0.95 (0.88, 1.03) | 0.98 (0.76, 1.25) | 0.25 |
| Model 2b | 1 (ref) | 1.01 (0.94, 1.09) | 0.99 (0.92, 1.07) | 1.05 (0.82, 1.36) | 0.88 |
| Model 3c | 1 (ref) | 1.02 (0.95, 1.10) | 1.00 (0.93, 1.09) | 1.07 (0.84, 1.38) | 0.69 |
|
| |||||
| NHS II | |||||
| No. of cases | 4,233 | 478 | 388 | 50 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 1.01 (0.92, 1.11) | 0.95 (0.85, 1.05) | 1.20 (0.91, 1.59) | 0.95 |
| Model 2b | 1 (ref) | 1.01 (0.92, 1.11) | 0.93 (0.84, 1.03) | 1.22 (0.92, 1.62) | 0.88 |
| Model 3c | 1 (ref) | 1.02 (0.93, 1.13) | 0.95 (0.85, 1.06) | 1.28 (0.96, 1.70) | 0.66 |
|
| |||||
| HPFS | |||||
| No. of cases | 8,886 | 999 | 856 | 92 | |
| RR (95% CI) | |||||
| Model 1a | 1 (ref) | 0.98 (0.92, 1.05) | 0.95 (0.88, 1.01) | 0.86 (0.70, 1.06) | 0.04 |
| Model 2b | 1 (ref) | 1.00 (0.93, 1.06) | 0.95 (0.89, 1.04) | 0.93 (0.75, 1.14) | 0.18 |
| Model 3c | 1 (ref) | 1.00 (0.94, 1.07) | 0.96 (0.91, 1.05) | 0.95 (0.77, 1.17) | 0.36 |
|
| |||||
| Pooled results | |||||
| RR (95% CI) | 1 (ref) | 1.01 (0.97, 1.06) | 0.98 (0.94, 1.03) | 1.07 (0.90, 1.26) | 0.97 |
| P heterogeneity | 0.91 | 0.74 | 0.25 | 0.59 | |
Abbreviation: CI, confidence interval; HPFS, Health Professionals Follow-up Study; NHS, Nurses’ Health Study
Age-adjusted.
Adjusted for the same sets of covariates as for model 2 and model 3 in table 2
Adjusted for the same sets of covariates as for model 2 and model 3 in table 2
In terms of the specific cancer sites, total rice consumption was not associated with risk of prostate, colorectal, lung, kidney cancer in any of these cohorts separately or pooled analyses (Table 5). For bladder cancer, borderline significant positive associations were seen with intake of total rice in both NHS and HPFS (pooled RR = 1.32, 95% CI 0.99-1.76; P for trend 0.09). For prostate cancer, the results did not change materially after excluding participants diagnosed with organ-confined tumor (RR for total rice consumption ≥ 5 vs. < 1 servings/wk: 1.06; 95% CI: 0.79-1.42; P for trend 0.76).
Table 5.
Risk of Specific Sites of Cancer According to Total Rice Intake in the HPFS, NHS I, and NHS II
| Total Rice Intake, No. of Servings | ||||||
|---|---|---|---|---|---|---|
| No. | < 1/week | 1/week | 2-4/week | ≥ 5/week | p-value | |
|
Prostate
|
||||||
| HPFS | 5,060 | 1 (ref) | 1.03 (0.96, 1.11) | 1.00 (0.93, 1.07) | 1.02 (0.91, 1.15) | 0.86 |
|
Breast
|
||||||
| NHS | 5,714 | 1 (ref) | 0.97 (0.91, 1.04) | 1.00 (0.94, 1.07) | 1.03 (0.89, 1.20) | 0.64 |
| NHS II | 2,401 | 1 (ref) | 0.91 (0.81, 1.02) | 0.95 (0.85,1.05) | 0.80 (0.67, 0.96) | 0.04 |
| Pooled | 1 (ref) | 0.95 (0.88, 1.03) | 0.99 (0.93, 1.04) | 0.90 (0.70, 1.16) | 0.48 | |
|
Colorectal
|
||||||
| NHS | 1,352 | 1 (ref) | 1.02 (0.89, 1.18) | 1.02 (0.88, 1.16) | 0.99 (0.71, 1.38) | 0.96 |
| HPFS | 1,042 | 1 (ref) | 0.98 (0.83, 1.16) | 1.09 (0.93, 1.27) | 0.88 (0.66, 1.16) | 0.51 |
| Pooled | 1 (ref) | 1.01 (0.91, 1.13) | 1.04 (0.93, 1.15) | 0.91 (0.74, 1.13) | 0.57 | |
|
Melanoma
|
||||||
| NHS | 870 | 1 (ref) | 1.14 (0.97, 1.36) | 1.00 (0.84, 1.18) | 0.92 (0.60, 1.40) | 0.63 |
| NHS II | 538 | 1 (ref) | 0.94 (0.74, 1.18) | 0.90 (0.72, 1.12) | 0.93 (0.65, 1.33) | 0.59 |
| HPFS | 695 | 1 (ref) | 0.88 (0.71, 1.09) | 1.00 (0.83, 1.21) | 0.71 (0.51, 1.00) | 0.10 |
| Pooled | 1 (ref) | 0.99 (0.82, 1.19) | 0.96 (0.86, 1.07) | 0.81 (0.65, 0.99) | 0.06 | |
|
Lung
|
||||||
| NHS | 1,205 | 1 (ref) | 1.00 (0.86, 1.16) | 0.92 (0.79, 1.07) | 0.87 (0.58, 1.30) | 0.26 |
| HPFS | 742 | 1 (ref) | 0.88 (0.72, 1.07) | 0.90 (0.75, 1.09) | 0.87 (0.63, 1.21) | 0.35 |
| Pooled | 1 (ref) | 0.96 (0.85, 1.08) | 0.91 (0.81, 1.03) | 0.87 (0.67, 1.11) | 0.15 | |
|
Bladder
|
||||||
| NHS | 357 | 1 (ref) | 0.95 (0.70, 1.26) | 0.96 (0.74, 1.25) | 1.33 (0.74, 2.37) | 0.54 |
| HPFS | 592 | 1 (ref) | 1.06 (0.85, 1.32) | 1.07 (0.87, 1.32) | 1.31 (0.94, 1.83) | 0.12 |
| Pooled | 1 (ref) | 1.00 (0.84, 1.19) | 1.02 (0.87, 1.20) | 1.32 (0.99, 1.76) | 0.09 | |
|
Kidney
|
||||||
| NHS | 268 | 1 (ref) | 1.37 (1.00, 1.87) | 1.15 (0.84, 1.56) | 1.20 (0.58, 2.48) | 0.52 |
| HPFS | 272 | 1 (ref) | 0.95 (0.69, 1.30) | 0.87 (0.64, 1.18) | 0.73 (0.42, 1.27) | 0.24 |
| Pooled | 1 (ref) | 1.15 (0.77, 1.71) | 1.02 (0.75, 1.39) | 0.90 (0.57, 1.41) | 0.85 | |
Abbreviation: CI, confidence interval; HPFS, Health Professionals Follow-up Study; NHS, Nurses’ Health Study All the models were adjusted for age (years), ethnicity (European Americans, Asian, African American, other), body mass index (calculated as weight in kilograms divided by height in meters squared; < 21.0, 21.0-22.9, 23.0-24.9, 25.0-26.9, 27.0-29.9, 30.0-32.9, 33.0-34.9, or ≥ 35.0), smoking status (never smoked, past smokers, current smokers 1-14 cigarettes/day, 15-24 cigarettes/day, or ≥ 25 cigarettes/day), physical activity (MET-hours/week, in quintiles), family history of cancer (yes or no), multivitamin supplementation (yes or no), total energy intake (kilocalories/day, in quintiles), consumption of fruit, vegetables, red meat, fish, nuts, whole grain (except brown rice), sugar-sweetened beverage (all in quintiles). For women, postmenopausal hormone use (yes or no) was further adjusted for.
In the sensitivity analyses, we found similar results after restricting our analyses within European Americans, never smokers, applying 4 to 8 years lag in updating dietary intakes, or stratified analyses according to BMI (Supplemental table 1). In addition, rice consumption was not associated with risk of bladder cancer by smoking status or breast cancer by menopausal status (Supplemental table 2).
Discussion
During up 18 to 26 years follow-up for over 280,000 US men and women, results from 3 prospective cohorts suggested the intakes of total rice, white rice or brown rice were not significantly associated with the risk of overall cancers. The null association remained among European American participants, never smokers, and after stratifying by BMI.
While arsenic and inorganic arsenic are carcinogenic to humans, it remains unknown whether arsenic associated with rice consumption increases risks of developing cancers. Hence, we conducted this first study to specifically address the question whether amounts of arsenic in rice are sufficient to see a detectable increase in cancer risk. Our study found no association between long-term rice consumption and overall cancer risk. To our knowledge, this study is the only analysis to date to assess the associations between the rice consumption and the risk of overall cancers. The age-adjusted null results were essentially similar to multivariable results. Additionally, the null results were observed in both genders and even among individuals with regular intake for decades. The highest category of rice intake in our study was at least 5 servings per week, which is approximately equivalent to 9.5μg/day inorganic arsenic from white rice, or 20.1μg/day from brown rice (1 serving = 1 cup ≈ 158 g cooked white rice or 195 g cooked brown rice 40). These amounts of arsenic in our study were comparable with those based on the Consumer Reports, which have shown that the average inorganic arsenic level is 13.3μg/cup in white rice and 28.2μg/cup in brown rice 7).
With regard to cancer sites, our study did not observe a statistically significant association between rice consumption and risk of any each specific cancer. However, it worthwhile noting that we observed a borderline significant increased risk of bladder cancer comparing ≥ 5/week vs. <1 week of total rice intake (RR= 1.32, 95% CI: 0.99, 1.76). While we did not directly measure arsenic in this study, bladder cancer is arguably the most susceptible cancer site to arsenic exposure although studies on bladder cancer and arsenic in low concentrations have been inconsistent 41,42. Clearly, our observation of borderline significant associations between rice intake and bladder cancer risk clearly warrants further investigation.
Strengths of our study include the large population, prospective design with decades of follow-up, repeated assessments of rice consumption, parallel analyses among men and women, and control for many risk factors for cancers. Limitations of this study merit consideration. First, our study did not directly measure arsenic levels in rice or other foods. Instead, this study addressed the specific question of whether the amounts of arsenic in rice are sufficient to see a detectable increase in cancer risk. We acknowledge that studies of arsenic are clearly desirable, but possibly require a biomarker. Second, measurement errors using SFFQs to assess rice intake exist. However, the correlations (r~0.5) between the SFFQs and multiple 1-week dietary records suggested that rice consumption was reasonably assessed in current study. Thirdly, our results should be generalized to other population with caution because most of our study participants are of European origin. The rice products consumed by our European-American participants were much less than those eaten by Asian, Hispanic and Indian populations. In addition, we have no information on where the rice was produced in the US, and arsenic levels in rice may vary by place of production, rice cooking methods, and the quality of water used to cook rice. Fourthly, as with all observational studies, residual confounding by other factors cannot be totally excluded; however, the consistently observed null results in both men and women argued against missing strong associations. Lastly, while our sample sizes are large overall, we had limited power to examine the potential effect of rice consumption on certain cancer sites with relatively low incidence in the US.
In summary, we did not find statistically significant associations between rice consumption and overall cancer risk in adult men or women. Future research to combine measuring levels of arsenic with amounts of rice consumption is warranted to better evaluate the effect of arsenic ingested from food on cancer risk.
Supplementary Material
BRIEF DESCRIPTION OF NOVELTY AND IMPACT OF PAPER.
We conducted the first study to comprehensively examine the associations between consumption of total rice, white rice and brown rice and risk of developing cancers. Results from this study suggest that long-term consumption of total rice, white rice or brown rice was not associated with risk of developing cancers in US men and women. Future research to combine measuring levels of arsenic with amounts of rice consumption is warranted.
Acknowledgements
We would like to thank the participants and staff of the Nurses’ Health Study and Nurses’ Health Study II, and Health Professionals Follow-up Study, for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. This work was supported by the National Institutes of Health (NIH) grants CA87969 and CA55075. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Footnotes
Conflict of interest:
None. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
Author’s contribution:
Drs Ran Zhang and Xuehong Zhang had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Zhang, Zhang, Wu, Wu, Sun, Hu, Han, Willett and Giovannucci
Acquisition of data: Willett and Giovannucci
Analysis and interpretation of data: Zhang, Zhang, Wu, Wu, Sun, Hu, Han, Willett and Giovannucci
Drafting of the manuscript: Ran Zhang and Xuehong Zhang
Statistical analysis: Ran Zhang and Xuehong Zhang
Obtained funding: Willett and Giovannucci
Administrative, technical, or material support: Willett and Giovannucci
Study supervision: Willett and Giovannucci
Critical revision of the manuscript for important intellectual content: Zhang, Zhang, Wu, Wu, Sun, Hu, Han, Willett and Giovannucci
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