Determinants of non attendance to mammography program in a region with high voluntary health insurance coverage

<p>Abstract</p> <p>Background</p> <p>High participation rates are needed to ensure that breast cancer screening programs effectively reduce mortality. We identified the determinants of non-participation in a public breast cancer screening program.</p> <p>Methods</p> <p>In this case-control study, 274 women aged 50 to 64 years included in a population-based mammography screening program were personally interviewed. Socio-demographic characteristics, health beliefs, health service utilization, insurance coverage, prior mammography and other preventive activities were examined.</p> <p>Results</p> <p>Of the 192 cases and 194 controls contacted, 101 and 173, respectively, were subsequently interviewed. Factors related to non-participation in the breast cancer screening program included higher education (odds ratio [OR] = 5.28; 95% confidence interval [CI95%] = 1.57–17.68), annual dental checks-ups (OR = 1.81; CI95%1.08–3.03), prior mammography at a private health center (OR = 7.27; CI95% 3.97–13.32), gynecologist recommendation of mammography (OR = 2.2; CI95%1.3–3.8), number of visits to a gynecologist (median visits by cases = 1.2, versus controls = 0.92, P = 0.001), and supplemental private insurance (OR = 5.62; CI95% = 3.28–9.6). Among women who had not received a prior mammogram or who had done so at a public center, perceived barriers were the main factors related to non-participation. Among women who had previously received mammograms at a private center, supplemental private health insurance also influenced non-participation. Benign breast symptoms increased the likelihood of participation.</p> <p>Conclusion</p> <p>Our data indicate that factors related to the type of insurance coverage (such as prior mammography at a private health center and supplemental private insurance) influenced non-participation in the screening program.</p

Energy Sprawl or Energy Efficiency: Climate Policy Impacts on Natural Habitat for the United States of America

Concern over climate change has led the U.S. to consider a cap-and-trade system to regulate emissions. Here we illustrate the land-use impact to U.S. habitat types of new energy development resulting from different U.S. energy policies. We estimated the total new land area needed by 2030 to produce energy, under current law and under various cap-and-trade policies, and then partitioned the area impacted among habitat types with geospatial data on the feasibility of production. The land-use intensity of different energy production techniques varies over three orders of magnitude, from 1.9–2.8 km2/TW hr/yr for nuclear power to 788–1000 km2/TW hr/yr for biodiesel from soy. In all scenarios, temperate deciduous forests and temperate grasslands will be most impacted by future energy development, although the magnitude of impact by wind, biomass, and coal to different habitat types is policy-specific. Regardless of the existence or structure of a cap-and-trade bill, at least 206,000 km2 will be impacted without substantial increases in energy efficiency, which saves at least 7.6 km2 per TW hr of electricity conserved annually and 27.5 km2 per TW hr of liquid fuels conserved annually. Climate policy that reduces carbon dioxide emissions may increase the areal impact of energy, although the magnitude of this potential side effect may be substantially mitigated by increases in energy efficiency. The possibility of widespread energy sprawl increases the need for energy conservation, appropriate siting, sustainable production practices, and compensatory mitigation offsets

Applying a new concept of embedding qualitative research: An example from a quantitative study of carers of people in later stage dementia

BACKGROUND: Qualitative methods are increasingly included in larger studies to provide a richer understanding of people's experience. This paper explores the potential of using a novel approach to embedded qualitative design as part of an observational study examining the effectiveness of home support for people in later stage dementia in England. The method involved collecting and analysing unsolicited conversational comments made by participants as they completed standardised measures. An evaluation of the method is presented using the voices of participants to illustrate its potential. METHODS: The conversations of 17 carers recruited to an observational study were audio recorded to gather commentary made while completing a structured interview. Data were interrogated using thematic analysis to investigate the feasibility of conducting an embedded qualitative study, the potential richness of the material and participants' reactions to formal questioning and participating in research. RESULTS: The findings revealed that qualitative data were available from this approach. Analysis generated three themes from carers: conflicting carer emotions; the importance of maintaining normality and agency within day-to-day life; and tensions between these desires and making use of formal services. Important issues for carers were revealed establishing the benefit of using the method. The advantages of exploiting unsolicited conversation included enhancing understanding of people's lived experience, reducing participant burden in research and easing the process of data collection. In addition, it provided an opportunity to evaluate individuals' experience of the research process. CONCLUSIONS: The findings demonstrate how unsolicited comments during structured interviews may appear incidental but can reveal important aspects of living with dementia. The method also emphasised methodological challenges for research in dementia, including the influence and impact of the research context. Further research is required to evaluate the method with other groups including people with dementia themselves

OptForce: An Optimization Procedure for Identifying All Genetic Manipulations Leading to Targeted Overproductions

Computational procedures for predicting metabolic interventions leading to the overproduction of biochemicals in microbial strains are widely in use. However, these methods rely on surrogate biological objectives (e.g., maximize growth rate or minimize metabolic adjustments) and do not make use of flux measurements often available for the wild-type strain. In this work, we introduce the OptForce procedure that identifies all possible engineering interventions by classifying reactions in the metabolic model depending upon whether their flux values must increase, decrease or become equal to zero to meet a pre-specified overproduction target. We hierarchically apply this classification rule for pairs, triples, quadruples, etc. of reactions. This leads to the identification of a sufficient and non-redundant set of fluxes that must change (i.e., MUST set) to meet a pre-specified overproduction target. Starting with this set we subsequently extract a minimal set of fluxes that must actively be forced through genetic manipulations (i.e., FORCE set) to ensure that all fluxes in the network are consistent with the overproduction objective. We demonstrate our OptForce framework for succinate production in Escherichia coli using the most recent in silico E. coli model, iAF1260. The method not only recapitulates existing engineering strategies but also reveals non-intuitive ones that boost succinate production by performing coordinated changes on pathways distant from the last steps of succinate synthesis

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2&nbsp;m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315&nbsp;cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\ub0C (mean&nbsp;=&nbsp;3.0&nbsp;\ub1&nbsp;2.1\ub0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6&nbsp;\ub1&nbsp;2.3\ub0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler ( 120.7&nbsp;\ub1&nbsp;2.3\ub0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km &lt;sup&gt;2&lt;/sup&gt; resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km &lt;sup&gt;2&lt;/sup&gt; pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications