Cancer remains the second leading cause of death in the United States, and the numbers of cases are expected to continue to rise worldwide. Cancer prevention strategies are crucial for reducing the cancer burden. The carcinogenic potential of dietary acrylamide exposure from cooked foods is unknown. Acrylamide is a by-product of the common Maillard reaction where reducing sugars (i.e., fructose and glucose) react with the amino acid, asparagine. Based on the evidence of acrylamide carcinogenicity in animals, the International Agency for Research on Cancer has classified acrylamide as a group 2A carcinogen for humans. Since the discovery of acrylamide in foods in 2002, a number of studies have explored its potential as a human carcinogen. This paper outlines a systematic review of dietary acrylamide and human cancer, acrylamide exposure and internal dose, exposure assessment methods in the epidemiologic studies, existing data gaps, and future directions. A majority of the studies reported no statistically significant association between dietary acrylamide intake and various cancers, and few studies reported increased risk for renal, endometrial, and ovarian cancers; however, the exposure assessment has been inadequate leading to potential misclassification or underestimation of exposure. Future studies with improved dietary acrylamide exposure assessment are encouraged.

Objective Nitrate and nitrite are probable human carcinogens when ingested under conditions that increase the formation of N-nitroso compounds. There have been limited efforts to develop US databases of dietary nitrate and nitrite for standard FFQ. Here we describe the development of a dietary nitrate and nitrite database and its calibration. Design We analysed data from a calibration study of 1942 members of the NIH–AARP (NIH–AARP, National Institutes of Health–AARP) Diet and Health Study who reported all foods and beverages consumed on the preceding day in two non-consecutive 24 h dietary recalls (24HR) and completed an FFQ. Based on a literature review, we developed a database of nitrate and nitrite contents for foods reported on these 24HR and for food category line items on the FFQ. We calculated daily nitrate and nitrite intakes for both instruments, and used a measurement error model to compute correlation coefficients and attenuation factors for the FFQ-based intake estimates using 24HR-based values as reference data. Results FFQ-based median nitrate intake was 68·9 and 74·1 mg/d, and nitrite intake was 1·3 and 1·0 mg/d, in men and women, respectively. These values were similar to 24HR-based intake estimates. Energy-adjusted correlation coefficients between FFQ- and 24HR-based values for men and women respectively were 0·59 and 0·57 for nitrate and 0·59 and 0·58 for nitrite; energy-adjusted attenuation factors were 0·59 and 0·57 for nitrate and 0·47 and 0·38 for nitrite. Conclusions The performance of the FFQ in assessing dietary nitrate and nitrite intakes is comparable to that for many other macro- and micronutrients.

Cancer is a leading cause of death worldwide, and the numbers of new cancer cases are expected to continue to rise. The main goals of cancer therapy include removing the primary tumor, preventing the spread of distant metastases, and improving survival and quality of life for the patients. To attain these goals of cancer therapy, the combination of different chemotherapeutics, as opposed to the conventional single-agent treatment, is an emerging area of research. Given the potential risks of drug toxicity in such treatment, the focus is to have a second compound that increases the anti-cancer potential of the primary agent but which reduces toxicity. There is an ever growing interest in treatment with natural compounds, such as plant phytoestrogens, as an adjuvant cancer therapy along with conventional cancer therapy. The question remains whether or not adding these compounds to the cancer therapy regimen as a second agent would be beneficial, and if they are safe to be used among cancer patients. The current literature suggests that phytoestrogen treatment is capable of inducing G2/M cell cycle arrest in a number of cancer cell lines, as well as up regulating cell cycle inhibitory molecules. Phytoestrogen therapy has been shown to inhibit inflammation, angiogenesis and metastases in various in vivo tumor models, and pronounced benefits observed when combined with radiation therapy. The lack of side effects from phase I and II clinical trials of phytoestrogens in cancer therapy points towards their safety, but to further understand their added benefit clinical studies with large sample sizes are required. We reviewed the recent research studies in these areas in an attempt to find evidence for their role in cancer therapy as well as safety.

BackgroundTobacco consumption constitutes a sizable portion of household consumption expenditure, which can lead to reduced expenditures on other basic commodities. This is known as the crowding-out effect. This study analyzes the crowding-out effect of tobacco consumption in Bangladesh, and the research findings have relevance for strengthening the tobacco control for improving health and well-being.MethodsWe analyzed data from the Bangladesh Household Income and Expenditure Survey 2010 to examine the differences in consumption expenditure pattern between tobacco user and non-user households. We further categorize tobacco user households in three mutually exclusive groups of smoking-only, smokeless-only, and dual (both smoking and smokeless); and investigated the crowding-out effects for these subgroups. We compared the mean expenditure shares of different types of households, and then estimated the conditional Engel curves for various expenditure categories using Seemingly Unrelated Regression (SUR) method. Crowding-out was considered to have occurred if estimated coefficient of the tobacco use indicator was negative and statistically significant.ResultsWe find that tobacco user households on average allocated less in clothing, housing, education, energy, and transportation and communication compared to tobacco non-user households. The SUR estimates also confirmed crowding-out in these consumption categories. Mean expenditure share of food and medical expenditure of tobacco user households, however, are greater than those of tobacco non-user households. Albeit similar patterns observed for different tobacco user households, there were differences in magnitudes depending on the type of tobacco-use, rural-urban locations and economic status.ConclusionPolicy measures that reduce tobacco use could reduce displacement of commodities by households with tobacco users, including those commodities that can contribute to human capital investments.