Cancer-related diagnostic and treatment capabilities of hospitals in the context of racial residential segregation.

OBJECTIVE: To evaluate distribution of hospital-level cancer diagnosis and treatment technologies along dimensions of racial residential segregation. STUDY DESIGN: Cross-sectional analysis of residential segregation and availability of technologies associated with cancer diagnosis and treatment. METHODS: American Hospital Association data were merged with American Community Survey data, and hospital was the unit of analysis. Isolation index and Atkinson's index were calculated for racial residential segregation for the census tract in which the hospital is located based on the composite census block groups. Logistic regression was used to model presence of cancer technologies as a function of percent below poverty (scaled 1-10), number of neighboring hospitals, and rural status. RESULTS: Segregation measured by isolation index was associated with the availability of some technologies, independent of percentage below 125% poverty line, number of neighboring hospitals, and rural status. Diagnostic cancer technologies, such as CT scan (odds ratio [OR] = 0.928, 95% confidence interval [CI]: 0.894, 0.964), ultrasound (OR = 0.961, 95% CI: 0.927, 0.997), mammography (OR = 0.943, 95% CI: 0.914, 0.974), optical colonoscopy (OR = 0.932, 95% CI: 0.904, 0.961), and full-field digital mammography (OR = 0.948, 95% CI: 0.920, 0.977) and therapeutic cancer technology such as chemo therapy (OR = 0.963, 95% CI: 0.934, 0.992) appear to be less available in neighborhoods with higher isolation index. However, when segregation is measured by Atkinson's index, CT scan (OR = 1.064, 95% CI: 1.010, 1.121), ultrasound (OR = 1.087, 95% CI: 1.035, 1.141), mammography (OR = 1.094, 95% CI: 1.049, 1.141), and optical colonoscopy (OR = 1.053, 95% CI: 1.012, 1.095) are more available in neighborhoods with higher Atkinson's index. CONCLUSION: These results suggest that cancer diagnostic capabilities in segregated areas are in the pathway between residential segregation and cancer treatment process, and future studies should evaluate individual-level associations.

Obesity prevalence in relation to gut microbial environments capable of producing equol or O-desmethylangolensin from the isoflavone daidzein.

BACKGROUND/OBJECTIVES: Studies have observed associations between the gut microbiome and obesity. O-desmethylangolensin (ODMA) and equol are gut bacterial metabolites of daidzein, a compound found in high amounts in soy foods. Approximately 80-95% and 25-60% of individuals harbor gut microbial communities capable of producing ODMA or equol, respectively. Given that other phenotypes of gut bacterial metabolism of dietary compounds have been associated with obesity, we hypothesized that daidzein-metabolizing phenotypes would be associated with obesity. The objective of this study was to compare the prevalence of ODMA-producer and equol-producer phenotypes in obese, overweight and normal-weight individuals. SUBJECTS/METHODS: Adults aged 18-95 years (n=297) provided a first-void urine sample after a 3-day soy challenge, and urinary ODMA and equol concentrations were used to classify individuals as producers or non-producers. Body mass index was calculated from self-reported weight and height. RESULTS: There were 60 ODMA non-producers and 173 equol non-producers. Obese individuals were 2.8 times more likely to be ODMA non-producers (odds ratio (OR)=2.8, 95% confidence interval (CI): 1.2, 6.2) compared with normal-weight individuals, when adjusted for age, race (white vs non-white), and gender and menopausal status (male, premenopausal female and postmenopausal female). Obesity was not associated with equol-producer phenotype (OR=1.1, 95% CI: 0.5, 2.2). Stronger associations with obesity were observed in the ODMA non-producers who were also equol producers than in the equol non-producers. CONCLUSIONS: Results from this analysis suggest that the ODMA-producer phenotype, but not equol-producer phenotype, is associated with obesity in adults. These results support further work to replicate these findings and evaluate the mechanisms of the observed associations.

Relationship of obesity and high urinary enterolignan concentrations in 6806 children and adults: analysis of National Health and Nutrition Examination Survey data.

The gut microbial environment (bacteria and metabolites) may have a role in obesity. Urinary enterolignan concentrations can provide a marker of interindividual differences in microbial environments. Analysis was conducted on 6806 individuals from 2003 to 2008 National Health and Nutrition Examination Survey data, and weight status, waist circumference groups and high- vs low-enterolignan concentration was evaluated using multinomial logistic regression, adjusted for personal and dietary factors. High-enterolignan concentrations were defined as the 90th percentile value and greater. High-enterodiol concentration was associated with 18% and 42% lower likelihood of being overweight and obese, respectively, and 48% lower likelihood of having high-risk waist circumference among adults. High-enterolactone concentration was associated with 24% and 64% lower likelihood of being overweight and obese, respectively. Age and sex were not modifiers of these associations. These results from a large human study population provide additional evidence supporting the microbiome-obesity relationship.

Intracranial meningioma and ionizing radiation in medical and occupational settings.

In a population-based case-control study of 200 cases and 400 controls in western Washington State, the authors assessed associations between meningioma and ionizing radiation in medical and occupational settings. No significant associations were observed for diagnostic studies or occupational settings, but associations were observed for radiation therapy to head or neck (odds ratio 3.7, 95% CI 1.5 to 9.5), especially for neoplastic conditions. Only four patients (2%) had meningiomas that followed high-dose cranial radiation.

Familial correlations, segregation analysis, and nongenetic correlates of soy isoflavone-metabolizing phenotypes.

Particular intestinal bacteria metabolize the soy isoflavone daidzein to equol and O-desmethylangolensin (O-DMA), metabolites that can be identified in urine. Individuals that harbor bacteria capable of producing equol or O-DMA are known as equol producers (approximately 30%-50% of the population) and O-DMA producers (approximately 80%-90% of the population), respectively. The equol-producer phenotype has been associated with sex hormone-related outcomes in several studies. However, the bacteria responsible for these phenotypes have not yet been identified and factors that influence the manifestation of these phenotypes are not well understood. To evaluate familial clustering of and nongenetic factors associated with these phenotypes, 410 individuals from 112 families participated in phenotyping (3-day soy challenge and Day 4 spot urine collection). In segregation analyses of the equol-producer phenotype, the Mendelian dominant model provided the most parsimonious fit to the data, suggesting that the pattern of inheritance of the equol-producer phenotype is consistent with an autosomal dominant trait. This phenotype was positively associated with education (p trend = 0.01), but not with sex, smoking, or several dietary factors. Results of the segregation analyses of the O-DMA-producer phenotype were inconclusive; no other models provided a more parsimonious fit to the data than the general model. This phenotype was inversely associated with age in a nonlinear model (p = 0.01), positively associated with age- and sex-adjusted height (odds ratio [OR] 10-cm increase = 0.38, 95% confidence interval [CI] = 0.15, 0.95) and body mass index (kg/m(2)) (OR = 0.91, 95% CI = 0.85, 0.96), but not with sex, education, smoking, or several dietary factors. These results suggest the equol-producer phenotype may be under some degree of genetic control and that there are likely other environmental factors not evaluated in the present analysis that contribute to both of these phenotypes. These results provide a foundation for further work to refine our understanding of heritable and environmental determinants of daidzein-metabolizing phenotypes.