Fruit and vegetable sources among ethnic groups

Objectives: Data are limited on how dietary sources of food and nutrients differ among ethnic groups. The objective of this study was to determine the main sources of fruit, vegetables, and vitamins A, C, and E for five ethnic groups. Methods: Dietary data were collected using a validated quantitative food frequency questionnaire from participants in the Multiethnic Cohort in Hawaii and Los Angeles County between 1993 and 1996. Data were analyzed for 186,916 participants representing five ethnic groups; African Americans, Japanese Americans, Native Hawaiians, Latinos, and Caucasians. Results: Lettuce was the most consumed vegetable (6.0%-9.9%) in all ethnic-sex groups, except African American women and Mexican-born Latino men and women. Oranges and bananas contributed more than one quarter to total fruit intake among all groups. Overall, more ethnic variation in food choices was observed for the top ten vegetables than fruit. The top sources for vitamins A, C and E were carrots, orange/grapefruit/pomelo and combined dishes, respectively. Between micronutrients studied, the greatest ethnic variation in foods consumed was observed among the top ten food sources of vitamin A. Conclusions: This is the first study providing data on the main types of fruit and vegetables consumed and the major sources of vitamins A, C, and E among these ethnic groups in the U.S. Such data are valuable for developing and implementing public health strategies to meet the USDA dietary recommendations and guiding ethnic-specific nutrition education and intervention programs

Ethnic differences in grains consumption and their contribution to intake of B-vitamins: results of the Multiethnic Cohort Study

Background: Research indicates that a diet rich in whole grains may reduce the risk of prevalent chronic diseases, including cardiovascular disease, diabetes, and some cancers, and that risk for these diseases varies by ethnicity. The objective of the current study was to identify major dietary sources of grains and describe their contribution to B vitamins in five ethnic groups. Methods. A cross-sectional mail survey was used to collect data from participants in the Multiethnic Cohort Study in Hawaii and Los Angeles County, United States, from 1993 to 1996. Dietary intake data collected using a quantitative food frequency questionnaire was available for 186,916 participants representing five ethnic groups (African American, Latino, Japanese American, Native Hawaiian and Caucasian) aged 45-75 years. The top sources of grain foods were determined, and their contribution to thiamin, riboflavin, niacin, vitamin B6, and folic acid intakes were analyzed. Results: The top source of whole grains was whole wheat/rye bread for all ethnic-sex groups, followed by popcorn and cooked cereals, except for Native Hawaiian men and Japanese Americans, for whom brown/wild rice was the second top source; major contributors of refined grains were white rice and white bread, except for Latinos. Refined grain foods contributed more to grain consumption (27.1-55.6%) than whole grain foods (7.4-30.8%) among all ethnic-sex groups, except African American women. Grain foods made an important contribution to the intakes of thiamin (30.2-45.9%), riboflavin (23.1-29.2%), niacin (27.1-35.8%), vitamin B6 (22.9-27.5%), and folic acid (23.3-27.7%). Conclusions: This is the first study to document consumption of different grain sources and their contribution to B vitamins in five ethnic groups in the U.S. Findings can be used to assess unhealthful food choices, to guide dietary recommendations, and to help reduce risk of chronic diseases in these populations

Postmenopausal Female Hormone Use and Estrogen Receptor–Positive and –Negative Breast Cancer in African American Women

Use of estrogen with progestin (combination therapy) is associated with increased incidence of estrogen receptor–positive (ER+) breast cancer in observational studies and randomized trials among postmenopausal white women. Whether this is also the case among African American women is not established

A case–control analysis of smoking and breast cancer in African American women: findings from the AMBER Consortium

Recent population studies suggest a role of smoking in the etiology of breast cancer, but few have been conducted among African American women. In a collaborative project of four large studies, we examined associations between smoking measures and breast cancer risk by menopause and hormone receptor status [estrogen receptor-positive (ER+), ER-negative (ER−) and triple-negative (ER−, PR−, HER2−)]. The study included 5791 African American women with breast cancer and 17376 African American controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in multivariable logistic regression analysis with adjustment for study and risk factors. Results differed by menopausal status. Among postmenopausal women, positive associations were observed for long duration and greater pack-years of smoking: relative to never smoking, fully adjusted ORs were 1.14 (95% CI: 1.03–1.26) for duration ≥20 years and 1.16 (95% CI: 1.01–1.33) for ≥20 pack-years. By contrast, inverse associations were observed among premenopausal women, with ORs of 0.80 (95% CI: 0.68–95) for current smoking and 0.81 (95% CI: 0.69–0.96) for former smoking, without trends by duration. Associations among postmenopausal women were somewhat stronger for ER+ breast cancer. The findings suggest that the relation of cigarette smoking to breast cancer risk in African American women may vary by menopausal status and breast cancer subtype

Association of selenium, tocopherols, carotenoids, retinol, and 15-isoprostane F(2t) in serum or urine with prostate cancer risk: the multiethnic cohort.

We examine the association of antioxidants and 15-isoprostane F(2t) with risk of prostate cancer.We conducted a nested case-control study of serum antioxidant biomarkers (selenium, tocopherols, carotenoids, and retinol) and a urinary oxidation biomarker (15-isoprostane F(2t)) with risk of prostate cancer within the Multiethnic Cohort. Demographic, dietary, and other exposure information was collected by self-administered questionnaire in 1993-1996. We compared prediagnostic biomarker levels from 467 prostate cancer cases and 936 cancer free controls that were matched on several variables. Multivariate conditional logistic regression models were used to compute adjusted odds ratios (ORs) and 95% confidence intervals (CIs).We observed that there was no overall association of serum concentrations of antioxidants and urinary concentrations of 15-isoprostane F(2t) with risk of prostate cancer or risk of advanced prostate cancer. However, we did observe an inverse association for serum selenium only among African-American men (p trend = 0.02); men in the third tertile of selenium concentrations had a 41% lower risk (95% CI: 0.38-0.93) of prostate cancer when compared to men in the first tertile.Overall, our study found no association of serum antioxidants or 15-isoprostane F(2t) with the risk of prostate cancer. The observed inverse association of selenium with prostate cancer in African-Americans needs to be validated in other studies

Predicting total, abdominal, visceral and hepatic adiposity with circulating biomarkers in Caucasian and Japanese American women.

Characterization of abdominal and intra-abdominal fat requires imaging, and thus is not feasible in large epidemiologic studies.We investigated whether biomarkers may complement anthropometry (body mass index [BMI], waist circumference [WC], and waist-hip ratio [WHR]) in predicting the size of the body fat compartments by analyzing blood biomarkers, including adipocytokines, insulin resistance markers, sex steroid hormones, lipids, liver enzymes and gastro-neuropeptides.Fasting levels of 58 blood markers were analyzed in 60 healthy, Caucasian or Japanese American postmenopausal women who underwent anthropometric measurements, dual energy X-ray absorptiometry (DXA), and abdominal magnetic resonance imaging. Total, abdominal, visceral and hepatic adiposity were predicted based on anthropometry and the biomarkers using Random Forest models.Total body fat was well predicted by anthropometry alone (R(2) = 0.85), by the 5 best predictors from the biomarker model alone (leptin, leptin-adiponectin ratio [LAR], free estradiol, plasminogen activator inhibitor-1 [PAI1], alanine transaminase [ALT]; R(2) = 0.69), or by combining these 5 biomarkers with anthropometry (R(2) = 0.91). Abdominal adiposity (DXA trunk-to-periphery fat ratio) was better predicted by combining the two types of predictors (R(2) = 0.58) than by anthropometry alone (R(2) = 0.53) or the 5 best biomarkers alone (25(OH)-vitamin D(3), insulin-like growth factor binding protein-1 [IGFBP1], uric acid, soluble leptin receptor [sLEPR], Coenzyme Q10; R(2) = 0.35). Similarly, visceral fat was slightly better predicted by combining the predictors (R(2) = 0.68) than by anthropometry alone (R(2) = 0.65) or the 5 best biomarker predictors alone (leptin, C-reactive protein [CRP], LAR, lycopene, vitamin D(3); R(2) = 0.58). Percent liver fat was predicted better by the 5 best biomarker predictors (insulin, sex hormone binding globulin [SHBG], LAR, alpha-tocopherol, PAI1; R(2) = 0.42) or by combining the predictors (R(2) = 0.44) than by anthropometry alone (R(2) = 0.29).The predictive ability of anthropometry for body fat distribution may be enhanced by measuring a small number of biomarkers. Studies to replicate these data in men and other ethnic groups are warranted

Alcohol Intake and Breast Cancer Risk in African American Women from the AMBER Consortium

Alcohol is a recognized risk factor for invasive breast cancer, but few studies involve African American women

Analysis of case-control association studies with known risk variants

Motivation: The question of how to best use information from known associated variants when conducting disease association studies has yet to be answered. Some studies compute a marginal P-value for each Several Nucleotide Polymorphisms independently, ignoring previously discovered variants. Other studies include known variants as covariates in logistic regression, but a weakness of this standard conditioning strategy is that it does not account for disease prevalence and non-random ascertainment, which can induce a correlation structure between candidate variants and known associated variants even if the variants lie on different chromosomes. Here, we propose a new conditioning approach, which is based in part on the classical technique of liability threshold modeling. Roughly, this method estimates model parameters for each known variant while accounting for the published disease prevalence from the epidemiological literature. Results: We show via simulation and application to empirical datasets that our approach outperforms both the no conditioning strategy and the standard conditioning strategy, with a properly controlled false-positive rate. Furthermore, in multiple data sets involving diseases of low prevalence, standard conditioning produces a severe drop in test statistics whereas our approach generally performs as well or better than no conditioning. Our approach may substantially improve disease gene discovery for diseases with many known risk variants. Availability: LTSOFT software is available online http://www.hsph.harvard.edu/faculty/alkes-price/software/ Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics onlin