33 research outputs found

    Fire and fuel hazard analysis in the Seeley Lake area Missoula County Montana

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    The associations of anthropometric, behavioural and sociodemographic factors with circulating concentrations of IGF-I, IGF-II, IGFBP-1, IGFBP-2, and IGFBP-3 in a pooled analysis of 16,024 men from 22 studies

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    Insulin‐like growth factors (IGFs) and insulin‐like growth factor binding proteins (IGFBPs) have been implicated in the aetiology of several cancers. To better understand whether anthropometric, behavioural and sociodemographic factors may play a role in cancer risk via IGF signalling, we examined the cross‐sectional associations of these exposures with circulating concentrations of IGFs (IGF‐I and IGF‐II) and IGFBPs (IGFBP‐1, IGFBP‐2 and IGFBP‐3). The Endogenous Hormones, Nutritional Biomarkers and Prostate Cancer Collaborative Group dataset includes individual participant data from 16,024 male controls (i.e. without prostate cancer) aged 22–89 years from 22 prospective studies. Geometric means of protein concentrations were estimated using analysis of variance, adjusted for relevant covariates. Older age was associated with higher concentrations of IGFBP‐1 and IGFBP‐2 and lower concentrations of IGF‐I, IGF‐II and IGFBP‐3. Higher body mass index was associated with lower concentrations of IGFBP‐1 and IGFBP‐2. Taller height was associated with higher concentrations of IGF‐I and IGFBP‐3 and lower concentrations of IGFBP‐1. Smokers had higher concentrations of IGFBP‐1 and IGFBP‐2 and lower concentrations of IGFBP‐3 than nonsmokers. Higher alcohol consumption was associated with higher concentrations of IGF‐II and lower concentrations of IGF‐I and IGFBP‐2. African Americans had lower concentrations of IGF‐II, IGFBP‐1, IGFBP‐2 and IGFBP‐3 and Hispanics had lower IGF‐I, IGF‐II and IGFBP‐3 than non‐Hispanic whites. These findings indicate that a range of anthropometric, behavioural and sociodemographic factors are associated with circulating concentrations of IGFs and IGFBPs in men, which will lead to a greater understanding of the mechanisms through which these factors influence cancer risk

    Use of an educational computer program before genetic counseling for breast cancer susceptibility: Effects on duration and content of counseling sessions

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    PURPOSE: Patients seeking genetic testing for inherited breast cancer risk are typically educated by genetic counselors; however, the growing demand for cancer genetic testing will likely exceed the availability of counselors trained in this area. We compared the effectiveness of counseling alone versus counseling preceded by use of a computer-based decision aid among women referred to genetic counseling for a family or personal history of breast cancer. METHODS: We developed and evaluated an interactive computer program that educates women about breast cancer, heredity, and genetic testing. Between May 2000 and September 2002, women at six study sites were randomized into either: Counselor Group (n = 105), who received standard genetic counseling, or Computer Group (n = 106), who used the interactive computer program before counseling. Clients and counselors both evaluated the effectiveness of counseling sessions, and counselors completed additional measures for the Computer Group. Counselors also recorded the duration of each session. RESULTS: Baseline characteristics did not differ significantly between groups. Participants and counselors both rated the counseling sessions as highly effective, whether or not the sessions were preceded by computer use. Computer use resulted in significantly shorter counseling sessions among women at low risk for carrying BRCA1/2 mutations. In approximately half of the sessions preceded by clients’ computer use, counselors indicated that clients’ use of the computer program affected the way they used the time, shifting the focus away from basic education toward personal risk and decision-making. CONCLUSION: This study shows that the interactive computer program “Breast Cancer Risk and Genetic Testing” is a valuable adjunct to genetic counseling. Its use before counseling can shorten counseling sessions and allow counselors to focus more on the clients’ individual risks and specific psychological concerns. As the demand for counseling services increases, a program such as this can play a valuable role in enhancing counseling efficiency

    State Disparities in Time Trends of Adolescent Body Mass Index Percentile and Weight-Related Behaviors in the United States

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    Evidence is conflicting as to whether youth obesity prevalence has reached a plateau in the United States overall. Trends vary by state, and experts recommend exploring whether trends in weight-related behaviors are associated with changes in weight status trends. Thus, our objective was to estimate between-state variation in time trends of adolescent body mass index (BMI) percentile and weight-related behaviors from 2001 to 2007. A time series design combined cross-sectional Youth Risk Behavior Survey data from 272,044 adolescents in 29 states from 2001 to 2007. Self-reported height, weight, sports participation, physical education, television viewing, and daily consumption of 100% fruit juice, milk, and fruits and vegetables were collected. Linear mixed models estimated state variance in time trends of behaviors and BMI percentile. Across states, BMI percentile trends were consistent despite differences in behavioral trends. Boys experienced a modest linear increase in BMI percentile (ÎČ = 0.18, 95% CI: 0.07, 0.30); girls experienced a non-linear increase, as the rate of increase declined over time from 1.02 units in 2001–2002 (95% CI: 0.68, 1.36) to 0.23 units in 2006–2007 (95% CI: −0.09, 0.56). States in which BMI percentile decreased experienced a greater decrease in TV viewing than states where BMI percentile increased. Otherwise, states with disparate BMI percentile trends did not differ with respect to behaviors. Future research should explore the role of other behaviors (e.g., soda consumption), measurement units (e.g., portion size), and societal trends (e.g., urban sprawl) on state and national adiposity trends
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