54 research outputs found

    Trends in absolute socioeconomic inequalities in mortality in Sweden and New Zealand. A 20-year gender perspective

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    BACKGROUND: Both trends in socioeconomic inequalities in mortality, and cross-country comparisons, may give more information about the causes of health inequalities. We analysed trends in socioeconomic differentials by mortality from early 1980s to late 1990s, comparing Sweden with New Zealand. METHODS: The New Zealand Census Mortality Study (NZCMS) consisting of over 2 million individuals and the Swedish Survey of Living Conditions (ULF) comprising over 100, 000 individuals were used for analyses. Education and household income were used as measures of socioeconomic position (SEP). The slope index of inequality (SII) was calculated to estimate absolute inequalities in mortality. Analyses were based on 3–5 year follow-up and limited to individuals aged 25–77 years. Age standardised mortality rates were calculated using the European population standard. RESULTS: Absolute inequalities in mortality on average over the 1980s and 1990s for both men and women by education were similar in Sweden and New Zealand, but by income were greater in Sweden. Comparing trends in absolute inequalities over the 1980s and 1990s, men's absolute inequalities by education decreased by 66% in Sweden and by 17% in New Zealand (p for trend <0.01 in both countries). Women's absolute inequalities by education decreased by 19% in Sweden (p = 0.03) and by 8% in New Zealand (p = 0.53). Men's absolute inequalities by income decreased by 51% in Sweden (p for trend = 0.06), but increased by 16% in New Zealand (p = 0.13). Women's absolute inequalities by income increased in both countries: 12% in Sweden (p = 0.03) and 21% in New Zealand (p = 0.04). CONCLUSION: Trends in socioeconomic inequalities in mortality were clearly most favourable for men in Sweden. Trends also seemed to be more favourable for men than women in New Zealand. Assuming the trends in male inequalities in Sweden were not a statistical chance finding, it is not clear what the substantive reason(s) was for the pronounced decrease. Further gender comparisons are required

    What potential has tobacco control for reducing health inequalities? The New Zealand situation

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    In this Commentary, we aim to synthesize recent epidemiological data on tobacco and health inequalities for New Zealand and present it in new ways. We also aim to describe both existing and potential tobacco control responses for addressing these inequalities. In New Zealand smoking prevalence is higher amongst Māori and Pacific peoples (compared to those of "New Zealand European" ethnicity) and amongst those with low socioeconomic position (SEP). Consequently the smoking-related mortality burden is higher among these populations. Regarding the gap in mortality between low and high socioeconomic groups, 21% and 11% of this gap for men and women was estimated to be due to smoking in 1996–99. Regarding the gap in mortality between Māori and non-Māori/non-Pacific, 5% and 8% of this gap for men and women was estimated to be due to smoking. The estimates from both these studies are probably moderate underestimates due to misclassification bias of smoking status. Despite the modest relative contribution of smoking to these gaps, the absolute number of smoking-attributable deaths is sizable and amenable to policy and health sector responses. There is some evidence, from New Zealand and elsewhere, for interventions that reduce smoking by low-income populations and indigenous peoples. These include tobacco taxation, thematically appropriate mass media campaigns, and appropriate smoking cessation support services. But there are as yet untried interventions with major potential. A key one is for a tighter regulatory framework that could rapidly shift the nicotine market towards pharmaceutical-grade nicotine (or smokeless tobacco products) and away from smoked tobacco

    Effects of childhood socioeconomic position on subjective health and health behaviours in adulthood: how much is mediated by adult socioeconomic position?

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    <p>Abstract</p> <p>Background</p> <p>Adult socioeconomic position (SEP) is one of the most frequently hypothesised indirect pathways between childhood SEP and adult health. However, few studies that explore the indirect associations between childhood SEP and adult health systematically investigate the mediating role of multiple individual measures of adult SEP for different health outcomes. We examine the potential mediating role of individual measures of adult SEP in the associations of childhood SEP with self-rated health, self-reported mental health, current smoking status and binge drinking in adulthood.</p> <p>Methods</p> <p>Data came from 10,010 adults aged 25-64 years at Wave 3 of the Survey of Family, Income and Employment in New Zealand. The associations between childhood SEP (assessed using retrospective information on parental occupation) and self-rated health, self-reported psychological distress, current smoking status and binge drinking were determined using logistic regression. Models were adjusted individually for the mediating effects of education, household income, labour market activity and area deprivation.</p> <p>Results</p> <p>Respondents from a lower childhood SEP had a greater odds of being a current smoker (OR 1.70 95% CI 1.42-2.03), reporting poorer health (OR 1.82 95% CI 1.39-2.38) or higher psychological distress (OR 1.60 95% CI 1.20-2.14) compared to those from a higher childhood SEP. Two-thirds to three quarters of the association of childhood SEP with current smoking (78%), and psychological distress (66%) and over half the association with poor self-rated health (55%) was explained by educational attainment. Other adult socioeconomic measures had much smaller mediating effects.</p> <p>Conclusions</p> <p>This study suggests that the association between childhood SEP and self-rated health, psychological distress and current smoking in adulthood is largely explained through an indirect socioeconomic pathway involving education. However, household income, area deprivation and labour market activity are still likely to be important as they are intermediaries in turn, in the socioeconomic pathway between education and health.</p

    Detecting referral and selection bias by the anonymous linkage of practice, hospital and clinic data using Secure and Private Record Linkage (SAPREL): case study from the evaluation of the Improved Access to Psychological Therapy (IAPT) service

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    Background: The evaluation of demonstration sites set up to provide improved access to psychological therapies (IAPT) comprised the study of all people identified as having common mental health problems (CMHP), those referred to the IAPT service, and a sample of attenders studied in-depth. Information technology makes it feasible to link practice, hospital and IAPT clinic data to evaluate the representativeness of these samples. However, researchers do not have permission to browse and link these data without the patients’ consent. Objective: To demonstrate the use of a mixed deterministic-probabilistic method of secure and private record linkage (SAPREL) - to describe selection bias in subjects chosen for in-depth evaluation. Method: We extracted, pseudonymised and used fuzzy logic to link multiple health records without the researcher knowing the patient’s identity. The method can be characterised as a three party protocol mainly using deterministic algorithms with dynamic linking strategies; though incorporating some elements of probabilistic linkage. Within the data providers’ safe haven we extracted: Demographic data, hospital utilisation and IAPT clinic data; converted post code to index of multiple deprivation (IMD); and identified people with CMHP. We contrasted the age, gender, ethnicity and IMD for the in-depth evaluation sample with people referred to IAPT, use hospital services, and the population as a whole. Results: The in IAPT-in-depth group had a mean age of 43.1 years; CI: 41.0 - 45.2 (n = 166); the IAPT-referred 40.2 years; CI: 39.4 - 40.9 (n = 1118); and those with CMHP 43.6 years SEM 0.15. (n = 12210). Whilst around 67% of those with a CMHP were women, compared to 70% of those referred to IAPT, and 75% of those subject to indepth evaluation (Chi square p< 0.001). The mean IMD score for the in-depth evaluation group was 36.6; CI: 34.2 - 38.9; (n = 166); of those referred to IAPT 38.7; CI: 37.9 - 39.6; (n = 1117); and of people with CMHP 37.6; CI 37.3- 37.9; (n = 12143). Conclusions: The sample studied in-depth were older, more likely female, and less deprived than people with CMHP, and fewer had recorded ethnic minority status. Anonymous linkage using SAPREL provides insight into the representativeness of a study population and possible adjustment for selection bias

    The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

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    The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths

    The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

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    The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.</p

    The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

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    The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.</p

    The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope. IV. Aperture Masking Interferometry

    Get PDF
    The James Webb Space Telescope’s Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 μm wavelengths, and a bright limit of ≃4 mag in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is ≃8 W2 (4.6 μm) magnitudes. AMI NRM and KPI achieve an inner working angle of ∼70 mas, which is well inside the ∼400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths

    The Near Infrared Imager and Slitless Spectrograph for the James Webb Space Telescope -- IV. Aperture Masking Interferometry

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    The James Webb Space Telescope's Near Infrared Imager and Slitless Spectrograph (JWST-NIRISS) flies a 7-hole non-redundant mask (NRM), the first such interferometer in space, operating at 3-5 \micron~wavelengths, and a bright limit of 4\simeq 4 magnitudes in W2. We describe the NIRISS Aperture Masking Interferometry (AMI) mode to help potential observers understand its underlying principles, present some sample science cases, explain its operational observing strategies, indicate how AMI proposals can be developed with data simulations, and how AMI data can be analyzed. We also present key results from commissioning AMI. Since the allied Kernel Phase Imaging (KPI) technique benefits from AMI operational strategies, we also cover NIRISS KPI methods and analysis techniques, including a new user-friendly KPI pipeline. The NIRISS KPI bright limit is 8\simeq 8 W2 magnitudes. AMI (and KPI) achieve an inner working angle of 70\sim 70 mas that is well inside the 400\sim 400 mas NIRCam inner working angle for its circular occulter coronagraphs at comparable wavelengths.Comment: 30 pages, 10 figure

    Crop Updates 2001 - Cereals

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    This session covers forty two papers from different authors: PLENARY 1. Planning your cropping program in season 2001, Dr Ross Kingwell, Agriculture Western Australia and University of Western Australia WORKSHOP 2. Can we produce high yields without high inputs? Wal Anderson, Centre for Cropping Systems, Agriculture Western Australia VARIETIES 3. Local and interstate wheat variety performance and $ return to WA growers, Eddy Pol, Peter Burgess and Ashley Bacon, Agritech Crop Research CROP ESTABLISHMENT 4 Soil management of waterlogged soils, D.M. Bakker, G.J. Hamilton, D. Houlbrooke and C. Spann, Agriculture Western Australia 5. Effect of soil amelioration on wheat yield in a very dry season, M.A Hamza and W.K. Anderson, Agriculture Western Australia 6. Fuzzy tramlines for more yield and less weed, Paul Blackwell1 and Maurice Black2 1Agriculture Western Australia, 2Harbour Lights Estate, Geraldton 7. Tramline farming for dollar benefits, Paul Blackwell, Agriculture Western Australia NUTRITION 8. Soil immobile nutrients for no-till crops, M.D.A. Bolland1, R.F. Brennan1,and W.L. Crabtree2, 1Agriculture Western Australia, 2Western Australian No-Tillage Farmers Association 9. Burn stubble windrows: to diagnose soil fertility problems, Bill Bowden, Chris Gazey and Ross Brennan, Agriculture Western Australia 10. Calcium: magnesium ratios; are they important? Bill Bowden1, Rochelle Strahan2, Bob Gilkes2 and Zed Rengel2 1Agriculture Western Australia, 2Department of Soil Science and Plant Nutrition, UWA 11. Responses to late foliar applications of Flexi-N, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 12. A comparison of Flexi-N placements, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 13. What is the best way to apply potassium? Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, CSBP futurefarm 14. Claying affects potassium nutrition in barley, Stephen Loss, David Phelps, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm 15. Nitrogen and potassium improve oaten hay quality, Stephen Loss, Tim O’Dea, Patrick Gethin, Ryan Guthrie, Lisa Leaver, CSBP futurefarm AGRONOMY 16. Agronomic responses of new wheat varieties in the northern wheatbelt, Darshan Sharma and Wal Anderson, Agriculture Western Australia 17. Wheat agronomy research on the south coast, Mohammad Amjad and Wal Anderson, Agriculture Western Australia 18. Influence of sowing date on wheat yield and quality in the south coast environment, Mohammad Amjadand Wal Anderson, Agriculture Western Australia 19. More profit from durum, Md.Shahajahan Miyan and Wal Anderson, Agriculture Western Australia 20. Enhancing recommendations of flowering and yield in wheat, JamesFisher1, Senthold Asseng2, Bill Bowden1 and Michael Robertson3 ,1AgricultureWestern Australia, 2CSIRO Plant Industry, 3CSIRO Sustainable Ecosystems 21. When and where to grow oats, Glenn McDonald, Agriculture Western Australia 22. Managing Gaidner barley for quality, Kevin Young and Blakely Paynter, Agriculture Western Australia PESTS AND DISEASES 23. Strategies for leaf disease management in wheat, Jatinderpal Bhathal1, Cameron Weeks2, Kith Jayasena1 and Robert Loughman1 ,1Agriculture Western Australia. 2Mingenew-Irwin Group Inc 24. Strategies for leaf disease management in malting barley, K. Jayasena1, Q. Knight2 and R. Loughman1, 1Agriculture Western Australia, 2IAMA Agribusiness 25. Cereal disease diagnostics, Dominie Wright and Nichole Burges, Agriculture Western Australia 26. The big rust: Did you get your money back!! Peter Burgess, Agritech Crop Research 27. Jockey – winning the race against disease in wheat, Lisa-Jane Blacklow, Rob Hulme and Rob Giffith, Aventis CropScience 28. Distribution and incidence of aphids and barley yellow dwarf virus in over-summering grasses in WA wheatbelt, Jenny Hawkes and Roger Jones, CLIMA and Agriculture Western Australia 29. Further developments in forecasting aphid and virus risk in cereals, Debbie Thackray, Jenny Hawkes and Roger Jones, Agriculture Western Australia and Centre for Legumes in Mediterranean Agriculture 30. Effect of root lesion nematodes on wheat yields in Western Australia, S. B. Sharma, S. Kelly and R. Loughman, Crop Improvement Institute, Agriculture Western Australia 31. Rotational crops and varieties for management of root lesion nematodes in Western Australia, S.B. Sharma, S. Kelly and R. Loughman, Crop Improvement Institute, Agriculture Western Australia WEEDS 32. Phenoxy herbicide tolerance of wheat, Peter Newman and Dave Nicholson, Agriculture Western Australia 33. Tolerance of wheat to phenoxy herbicides,Harmohinder S. Dhammu, Terry Piper and Mario F. D\u27Antuono, Agriculture Western Australia 34. Herbicide tolerance of durum wheats, Harmohinder S. Dhammu, Terry Piper and David Nicholson, Agriculture Western Australia 35. Herbicide tolerance of new wheats, Harmohinder S. Dhammu, Terry Piper and David F. Nicholson, Agriculture Western Australia BREEDING 36. Towards molecular breeding of barley: construction of a molecular genetic map, Mehmet Cakir1, Nick Galwey1, David Poulsen2, Garry Ablett3, Reg Lance4, Rob Potter5 and Peter Langridge6,1Plant Sciences, Faculty of Agriculture, UWA, 2Queensland Department of Primary Industries, Qld, 3Centre for Plant Conservation Genetics Southern Cross University, Lismore NSW, 5SABC Murdoch University, WA, 6Department of Plant Science University of Adelaide, Glen Osmond SA 37. Toward molecular breeding of barley: Identifying markers linked to genes for quantitative traits, Mehmet Cakir1, Nick Galwey1, David Poulsen2, Reg Lance3, Garry Ablett4, Greg Platz2, Joe Panozzo5, Barbara Read6, David Moody5, Andy Barr7 and Peter Langridge7 , 1Plant Sciences, Faculty of Agriculture, UWA, 2Queensland Department of Primary Industries, Warwick, QLD,3Agriculture Western Australia, 4Centre for Plant Conservation Genetics, Southern Cross University, Lismore NSW, 5VIDA Private Bag 260, Horsham VIC, 6NSW Dept. of Agriculture, Wagga Wagga NSW, 7Department of Plant Science, University of Adelaide, Glen Osmond SA 38. Can we improve grain yield by breeding for greater early vigour in wheat? Tina Botwright1, Tony Condon1, Robin Wilson2 and Iain Barclay2, 1CSIRO Plant Industry, 2Agriculture Western Australia MARKETING AND QUALITY 39. The Crop Improvement Royalty, Howard Carr, Agriculture Western Australia 40. GrainGuardÔ - The development of a protection plan for the wheat industry, Greg Shea, Agriculture Western Australia CLIMATE 41. Rainfall – what happened in 2000 and the prospects for 2001, Ian Foster, Agriculture Western Australia 42. Software for climate management issues, David Tennant,Agriculture Western Australia CONTRIBUTING AUTHOR CONTACT DETAIL
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