Construction and case study of a novel lung cancer risk index.

PURPOSE: This study constructs a lung cancer risk index (LCRI) that incorporates many modifiable risk factors using an easily reproducible and adaptable method that relies on publicly available data. METHODS: We used meta-analysis followed by Analytic Hierarchy Process (AHP) to generate a lung cancer risk index (LCRI) that incorporates seven modifiable risk factors (active smoking, indoor air pollution, occupational exposure, alcohol consumption, secondhand smoke exposure, outdoor air pollution, and radon exposure) for lung cancer. Using county-level population data, we then performed a case study in which we tailored the LCRI for use in the state of Illinois (LCRIIL). RESULTS: For both the LCRI and the LCRIIL, active smoking had the highest weights (46.1% and 70%, respectively), whereas radon had the lowest weights (3.0% and 5.7%, respectively). The weights for alcohol consumption were 7.8% and 14.7% for the LCRI and the LCRIIL, respectively, and were 3.8% and 0.95% for outdoor air pollution. Three variables were only included in the LCRI: indoor air pollution (18.5%), occupational exposure (13.2%), and secondhand smoke exposure (7.6%). The Consistency Ratio (CR) was well below the 0.1 cut point. The LCRIIL was moderate though significantly correlated with age-adjusted lung cancer incidence (r = 0.449, P < 0.05) and mortality rates (r = 0.495, P < 0.05). CONCLUSION: This study presents an index that incorporates multiple modifiable risk factors for lung cancer into one composite score. Since the LCRI allows data comprising the composite score to vary based on the location of interest, this measurement tool can be used for any geographic location where population-based data for individual risk factors exist. Researchers, policymakers, and public health professionals may utilize this framework to determine areas that are most in need of lung cancer-related interventions and resources.

Creation and Evaluation of the Illinois Cancer Risk Index as a Predictor of Four Common Cancers.

INTRODUCTION: Nearly half of all cancer deaths in the US are attributed to 4 common cancers: lung, colorectal, breast, and prostate. Illinois residents experience higher rates of cancer death from all 4 cancers compared with the US overall. We developed the Illinois Cancer Risk Index (ICRI), which incorporates many predictors of these cancers into a single summary measure, to identify Illinois counties that would benefit most from public health intervention. METHODS: We identified 90 county-level predictors of 4 common cancers, used multicollinearity testing to reduce this number to 61, and applied factor analysis to extract and analyze 4 factors representing 25 variables. Next, we created the ICRI by regressing the 4 factors on our outcome of interest - an age-adjusted common cancers mortality rate (CCMR), incorporating the direction of the ß-coefficients from regression models to sum factor scores. Finally, we mapped and assessed the geographic distributions of both ICRI and CCMR by county across the state. RESULTS: The ICRI was positively associated with the CCMR (r = 0.59, P < .001) and explained 32.2% of the variance in the CCMR across Illinois. The ICRI showed distinct geospatial patterns across the state, with the highest risk counties located in the east-central, far northern, and southern regions. The CCMR showed similar geospatial patterns. CONCLUSION: Our study identifies counties in Illinois that may benefit most from interventions that target multiple cancer risk factors simultaneously. The ICRI may be adapted for use in other geographic locations where data are available.

Association of anti-contagion policies with the spread of COVID-19 in United States.

BACKGROUND: The outbreak of a novel coronavirus, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or COVID-19, raised worldwide concern. The present study investigates the association between anti-contagion policies and the spread of COVID-19 across the United States. DESIGN AND METHODS: We selected the most frequently implemented COVID-19 anti-contagion policies in all the U.S. states issued from 29 February 2020. Accordingly, we modified an epidemiological model and combined it with a comprehensive statistical analysis to evaluate the policies' individual and overall likely impact. RESULTS: For the first time, a novel index, evaluates the associations between policy implementation and COVID-19 spread at both statewide and national levels. Our results indicate that governmental policies requiring mask use, businesses social distancing, and quarantining travelers may be most effective for controlling COVID-19 spread. Simultaneously, widespread orders like school closure and safer-at-home that can be particularly disruptive to the economy and social fabric of society may be unnecessary given their lack of association with reducing infection. CONCLUSIONS: The absence of any COVID-19 vaccines during the first several months of its pandemic necessitated using governmental policies to help stop the spread of this disease. Our index showed the association between implemented policies and COVID-19 spread, highlighting the specific policies with the greatest association - mandatory quarantine upon entering a state, businesses implementing social distancing, and mandatory mask use - and those with less association like school closure and safer-at-home orders. This study provided evidence to inform policy choices for the current global crisis and future pandemics.

Optimal siting of solid waste-to-value-added facilities through a GIS-based assessment.

Siting a solid waste conversion facility requires an assessment of solid waste availability as well as ensuring compliance with environmental, social, and economic factors. The main idea behind this study was to develop a methodology to locate suitable locations for waste conversion facilities considering waste availability as well as environmental and social constraints. A geographic information system (GIS) spatial analysis was used to identify the most suitable areas and to screen out unsuitable lands. The analytic hierarchy process (AHP) was used for a multi-criteria evaluation of relative preferences of different environmental and social factors. A case study was conducted for Alberta, a western province in Canada, by performing a province-wide waste availability assessment. The total available waste considered in this study was 4,077,514tonnes/year for 19 census divisions collected from 79 landfills. Finally, a location-allocation analysis was performed to determine suitable locations for 10 waste conversion facilities across the province.

Synbiotic (Biomin imbo) alters gut bacterial microflora of Russian sturgeon, Acipenser guldenstadti (Brandt & Ratzeburg, 1833) in a time-dependent pattern.

We investigated the efficiency of Synbiotic (Biomin imbo) in alternation and stabilization of gut microflora of Russian sturgeon, Acipenser guldenstadti. For this purpose, five experimental treatments and one control group with three replicates were considered. In treatment groups, fish were fed with diet containing 1 (T1), 1.5 (T2), 2 (T3), 2.5 (T4) and 3 (T5) g Synbiotic/kg diet. In control group, fish were fed without supplement of Synbiotic. Sampling for bacterial studies was conducted at days 20, 40 and 60 after the beginning of the experiment. According to results, there were no significant differences in total bacterial count between Synbiotic treatments and also in comparison with control group 20 days after the beginning of the experiment (P > 0.05). At days 40 and 60 of experiment, the highest total bacterial counts were observed in control and T1 group respectively. At day 20, the lactic acid bacteria count was higher significantly in Synbiotic treatments compared to control group (P < 0.05). In all sampling times (i.e. days 20, 40 and 60), the highest lactic acid bacteria count was observed in fish fed with 3 g Synbiotic/kg diet i.e. treatment 5 (P < 0.05). In each experimental group, total bacteria and lactic acid bacteria counts increased significantly as the duration of experiment expanded. In this regard, these parameters were significantly higher at day 60 compared to day 40 and 20 (P < 0.05). In conclusion, our results showed that Synbiotic (Biomin imbo) alters and stabilizes efficiently the microflora of Russian sturgeon gut towards lactic acid bacteria in a time-dependent pattern.

Development of a decision model for the techno-economic assessment of municipal solid waste utilization pathways.

Economic competitiveness is one of the key factors in making decisions towards the development of waste conversion facilities and devising a sustainable waste management strategy. The goal of this study is to develop a framework, as well as to develop and demonstrate a comprehensive techno-economic model to help county and municipal decision makers in establishing waste conversion facilities. The user-friendly data-intensive model, called the FUNdamental ENgineering PrinciplEs-based ModeL for Estimation of Cost of Energy and Fuels from MSW (FUNNEL-Cost-MSW), compares nine different waste management scenarios, including landfilling and composting, in terms of economic parameters such as gate fees and return on investment. In addition, a geographic information system (GIS) model was developed to determine suitable locations for waste conversion facilities and landfill sites based on integration of environmental, social, and economic factors. Finally, a case study on Parkland County and its surrounding counties in the province of Alberta, Canada, was conducted and a sensitivity analysis was performed to assess the influence of the key technical and economic parameters on the calculated results.