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Although biological evidence suggests that tea consumption may protect against non-Hodgkin lymphoma (NHL), epidemiological evidence has been unclear. The aim of this study was to examine the association between tea-drinking habits and the risk of NHL in a large nationwide prospective cohort of postmenopausal US women. 68 854 women who were enrolled from 1993 through 1998 in the Women's Health Initiative Observational Study and responded to year 3 annual follow-up questionnaire comprised the analytic cohort. Newly diagnosed NHL cases after the year 3 visit were confirmed by medical and pathology reports. Multivariable-adjusted Cox proportional hazards models were performed to assess the associations of tea-drinking habits (specifically, the amounts of caffeinated/herbal/decaffeinated tea intake) with the overall risk of NHL and three major subtypes (diffuse large B-cell lymphoma (n 195, 0·3 %), follicular lymphoma (n 128, 0·2 %) and chronic lymphocytic leukaemia/small lymphocytic lymphoma (n 51, 0·1 %)). Among 62 622 participants, a total of 663 (1·1 %) women developed NHL during a median follow-up of 16·51 (sd 6·20) years. Overall, different amounts of type-specific tea intake were not associated with the risk of NHL regardless of its histologic subtypes after adjustment for confounders. Our findings suggest that tea intake at the current consumption level does not influence the risk of NHL, regardless of its histologic types. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the relationship between red blood cell (RBC) polyunsaturated fatty acid (PUFA) levels, and dietary PUFA and fish intake, with prevalent and incident age-related macular degeneration (AMD) in a US cohort of postmenopausal women. Methods: This analysis included 1456 postmenopausal women from the Women's Health Initiative (WHI) Clinical Trials. RBC PUFAs were measured from fasting serum samples collected at WHI baseline. Dietary PUFAs and fish intake were assessed via food frequency questionnaires at baseline. There were 240 women who had prevalent AMD and 138 who self-reported AMD development over 9.5 years. Adjusted odds ratios and 95% confidence intervals were estimated for prevalent AMD by RBC PUFA levels, dietary PUFA intake, and frequency of fish consumption. Adjusted hazard ratios and 95% confidence intervals were estimated for incident AMD. A p-for-trend was estimated for continuous measures of dietary PUFA and fish intake. Results: No significant association was found between prevalent or incident AMD and RBC docosahexaenoic acid (DHA) + eicosapentaenoic acid (EPA), EPA, DHA, alpha-linolenic acid (ALA), linoleic acid (LA), or arachidonic acid (AA). A positive association was found between dietary intake of AA and odds of prevalent AMD (p-for-trend for continuous AA intake = 0.02) and between intake of LA/ALA and incident AMD (p-for-trend for continuous ratio of LA/ALA intake = 0.03). No statistically significant associations were found between AMD and dietary intake of PUFAs or fish. Conclusions: RBC PUFAs were not associated with AMD in this cohort. Overall, dietary analyses of PUFAs supported this, excepting dietary AA intake and intake of LA in proportion to ALA of which there were trends of increased risk. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has demonstrated promise in predicting mortality; however, understanding spatial variation in risk factor contributions to mortality rate requires explainability. We applied explainable artificial intelligence (XAI) on a stack-ensemble machine learning model framework to explore and visualize the spatial distribution of the contributions of known risk factors to lung and bronchus cancer (LBC) mortality rates in the conterminous United States. We used five base-learners—generalized linear model (GLM), random forest (RF), Gradient boosting machine (GBM), extreme Gradient boosting machine (XGBoost), and Deep Neural Network (DNN) for developing stack-ensemble models. Then we applied several model-agnostic approaches to interpret and visualize the stack ensemble model's output in global and local scales (at the county level). The stack ensemble generally performs better than all the base learners and three spatial regression models. A permutation-based feature importance technique ranked smoking prevalence as the most important predictor, followed by poverty and elevation. However, the impact of these risk factors on LBC mortality rates varies spatially. This is the first study to use ensemble machine learning with explainable algorithms to explore and visualize the spatial heterogeneity of the relationships between LBC mortality and risk factors in the contiguous USA. [ABSTRACT FROM AUTHOR]

BACKGROUND: In vitro and animal data suggest that cadmium, a heavy metal that contaminates some foods and tobacco plants, is an estrogenic endocrine disruptor. Elevated estrogen exposure is associated with breast, endometrial, and ovarian cancer risk. OBJECTIVES: We examined the association between dietary cadmium intake and risk of these cancers in the large, well-characterized Women's Health Initiative (WHI). METHODS: A total of 155,069 postmenopausal women, 50-79 years of age, who were enrolled in the WHI clinical trials or observational study, participated in this study. We estimated dietary cadmium consumption by combining baseline food frequency questionnaire responses with U.S. Food and Drug Administration data on food cadmium content. Participants reported incident invasive breast, endometrial, or ovarian cancer, and WHI centrally adjudicated all cases through August 2009. We applied Cox regression to estimate adjusted hazard ratios (HRs) and 95% CIs for each cancer, comparing quintiles of energy-adjusted dietary cadmium intake. RESULTS: Over an average of 10.5 years, 6,658 invasive breast cancers, 1,198 endometrial cancers, and 735 ovarian cancers were reported. We observed no statistically significant associations between dietary cadmium and risk of any of these cancers after adjustment for potential confounders including total dietary energy intake. Results did not differ in any subgroup of women examined. CONCLUSIONS: We found little evidence that dietary cadmium is a risk factor for breast, endometrial, or ovarian cancers in postmenopausal women. Misclassification in dietary cadmium assessment may have attenuated observed associations. CITATION: Adams SV, Quraishi SM, Shafer MM, Passarelli MN, Freney EP, Chlebowski RT, Luo J, Meliker JR, Mu L, Neuhouser ML, Newcomb PA. 2014. Dietary cadmium exposure and risk of breast, endometrial, and ovarian cancer in the Women's Health Initiative. Environ Health Perspect 122:594-600; http://dx.doi.org/10.1289/ehp.1307054 [ABSTRACT FROM AUTHOR]

Some preliminary studies indicate that components in coffee may have anticarcinogenic effects. However, the association between coffee-drinking habits and the risk of non-Hodgkin lymphoma (NHL) remain controversial. To examine the relationship between coffee intake and NHL incidence in a large prospective study of postmenopausal US women. The participants included 74,935 women from the Women's Health Initiative Observational Study who were recruited from 1993 through 1998. Information about coffee-drinking habits was collected at baseline via self-administered questionnaires. Newly diagnosed NHL was validated by medical records and pathology records. Separate analyses were performed for the following three subtypes of NHL: diffuse large B-cell lymphoma (n = 244), follicular lymphoma (n = 166), and chronic lymphocytic leukemia/small lymphocytic lymphoma (n = 64). Age-adjusted and multivariable-adjusted Cox proportional hazards models were used to determine associations of coffee intake (specifically, the total amount of coffee consumed daily, coffee types, and coffee preparation methods) with risk of NHL. A total of 851 women developed NHL during a median 18.34 years of follow-up (range = 0.01 to 24.30 years; ± 6.63 years). Overall, no associations were observed between coffee intake and risk of NHL regardless of the total amount of daily coffee intake (P value for trend = 0.90), caffeinated (P = 0.55) or decaffeinated coffee intake (P = 0.78), and filtered or unfiltered coffee intake (P = 0.91) after controlling for sociodemographic factors, lifestyle risk factors, and clinical risk factors/current medical conditions. No significant associations were observed between coffee intake with specific subtypes of NHL. A statistically significant interaction was found between alcohol intake, coffee intake, and incident NHL (P value for interaction = 0.02) based on the adjusted analysis. Specifically, among women who frequently consumed alcohol (> 7 drinks/week), those who had moderate coffee intake (2 to 3 c coffee/day) had a significantly reduced risk of developing NHL (hazard ratio 0.61, 95% CI 0.36 to 0.98), compared with those who did not drink coffee. The findings from this study do not support an association between coffee consumption and NHL risk, irrespective of the total amount of daily coffee intake, coffee types, or coffee preparation methods. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, social distancing measures often result in individual isolation, which can lead to adverse mental outcomes. We collected online questionnaires from 3,952 US adults to examine the impact of "shelter-in-place" guidelines on mental health, and to explore potential disparities and modifiable factors. Self-reported anxiety, depression, and PTSD symptoms were associated with more restrictive quarantine. Younger adults, women, those with lower income, more insecurity, more media exposure, reduced physical activity, or worsened family relationships were particularly affected. Targeted prevention on susceptible subpopulations, including young adults and lower SES groups, might help mitigate disparities in COVID-19-related mental health problems., (Copyright © 2021. Published by Elsevier B.V.)

Long-term PM 2.5 exposure might predispose populations to SARS-CoV-2 infection and intervention policies might interrupt SARS-CoV-2 transmission and reduce the risk of COVID-19. We conducted an ecologic study across the United States, using county-level COVID-19 incidence up to 12 September 2020, to represent the first two surges in the U.S., annual average of PM 2.5 between 2000 and 2016 and state-level facemask mandates and stay home orders. We fit negative binomial models to assess COVID-19 incidence in association with PM 2.5 and policies. Stratified analyses by facemask policy and stay home policy were also performed. Each 1-µg/m 3 increase in annual average concentration of PM 2.5 exposure was associated with 7.56% (95% CI: 3.76%, 11.49%) increase in COVID-19 risk. Facemask mandates and stay home policies were inversely associated with COVID-19 with adjusted RRs of 0.8466 (95% CI: 0.7598, 0.9432) and 0.9193 (95% CI: 0.8021, 1.0537), respectively. The associations between PM 2.5 and COVID-19 were consistent among counties with or without preventive policies. Our study added evidence that long-term PM 2.5 exposure increased the risk of COVID-19 during each surge and cumulatively as of 12 September 2020, in the United States. Although both state-level implementation of facemask mandates and stay home orders were effective in preventing the spread of COVID-19, no clear effect modification was observed regarding long-term exposure to PM 2.5 on the risk of COVID-19.

Living near major roadways has been associated with increased risk of cardiovascular morbidity and mortality, presumably from exposure to elevated levels of traffic-related air and/or noise pollution. This association may potentially be mediated through increased risk of incident hypertension, but results from prior studies are equivocal. Using Cox proportional hazards models we examined residential proximity to major roadways and incident hypertension among 38,360 participants of the Women's Health Initiative (WHI) Clinical Trial cohorts free of hypertension at enrollment and followed for a median of 7.9 years. Adjusting for participant demographics and lifestyle, trial participation, and markers of individual and neighborhood socioeconomic status, the hazard ratios for incident hypertension were 1.13 (95% CI: 1.00, 1.28), 1.03 (0.95, 1.11), 1.05 (0.99, 1.11), and 1.05 (1.00, 1.10) for participants living ≤50, >50-200, >200-400, and >400-1000 m vs >1000 m from the nearest major roadway, respectively (ptrend=0.013). This association varied substantially by WHI study region with hazard ratios for women living ≤50 m from a major roadway of 1.61 (1.18, 2.20) in the West, 1.51 (1.22, 1.87) in the Northeast, 0.89 (0.70, 1.14) in the South, and 0.94 (0.75, 1.19) in the Midwest. In this large, national cohort of post-menopausal women, residential proximity to major roadways was associated with incident hypertension in selected regions of the U.S. If causal, these results suggest residential proximity to major roadways, as a marker for air, noise and other traffic-related pollution, may be a risk factor for hypertension., (Copyright © 2015 Elsevier Inc. All rights reserved.)