Using Administrative Data to Count and Classify Households with Local Applications

Households rather than individuals are being increasingly used for research and to target and evaluate public policy. As a result accurate and timely household level statistics have become an increasing necessity especially at local level. However, official sources of information on households are fragmented with significant gaps and inaccuracies that limit their usefulness. This paper reviews present statistical arrangements and then describes a new approach to data collection and household classification which combine various local administrative sources. An intermediate step is the creation of local population counts which are converted into household types and these methods are described in two companion papers previously published in this journal. The utility and advantages of the approach are demonstrated using the example of the six Olympic London Boroughs for whom the data collection was undertaken in 2011 and the analysis subsequently

Swedish high school students' knowledge and attitudes regarding fertility and family building

<p>Abstract</p> <p>Background</p> <p>Infertility is a serious problem for those who suffer. Some of the risks for infertility are preventable and the individual should therefore have knowledge of them. The purposes of this study were to investigate high-school students' knowledge about fertility, plans for family building and to compare views and knowledge between female and male students.</p> <p>Methods</p> <p>A questionnaire containing 34 items was answered by 274 students. Answers from male and female students were compared using student's <it>t</it>-test for normally distributed variables and Mann-Whitney <it>U</it>-test for non-normal distributions. The chi-square test was used to compare proportions of male and female students who answered questions on nominal and ordinal scales. Differences were considered as statistically significant at a <it>p</it>-value of 0.05.</p> <p>Results</p> <p>Analyses showed that 234 (85%) intended to have children. Female students felt parenthood to be significantly more important than male students: <it>p </it>= <it><</it>0.01. The mean age at which the respondents thought they would like to start to build their family was 26 (± 2.9) years. Men believed that women's fertility declined significantly later than women did: <it>p </it>= <it><</it>0.01. Women answered that 30.7% couples were involuntarily infertile and men answered 22.5%: <it>p </it>= <it><</it>0.01. Females thought it significantly more likely that they would consider IVF or adoption than men, <it>p = </it>0.01. Men felt they were more likely to abstain from having children than women: <it>p = <</it>0.01. Women believed that body weight influenced fertility significantly more often than men: <it>p = <</it>0.01 and men believed significantly more often that smoking influenced fertility: <it>p </it>= 0.03. Both female and male students answered that they would like to have more knowledge about the area of fertility.</p> <p>Conclusions</p> <p>Young people plan to start their families when the woman's fertility is already in decline. Improving young people's knowledge about these issues would give them more opportunity to take responsibility for their sexual health and to take an active role in shaping political change to improve conditions for earlier parenthood.</p

HbA1C and Cancer Risk in Patients with Type 2 Diabetes – A Nationwide Population-Based Prospective Cohort Study in Sweden

Background: Diabetes is associated with increased cancer risk. The underlying mechanisms remain unclear. Hyperglycemia might be one risk factor. HbA1c is an indicator of the blood glucose level over the latest 1 to 3 months. This study aimed to investigate association between HbA1c level and cancer risks in patients with type 2 diabetes based on real life situations. Methods: This is a cohort study on 25,476 patients with type 2 diabetes registered in the Swedish National Diabetes Register from 1997-1999 and followed until 2009. Follow-up for cancer was accomplished through register linkage. We calculated incidences of and hazard ratios (HR) for cancer in groups categorized by HbA1c &lt;= 58 mmol/mol (7.5%) versus &gt;58 mmol/mol, by quartiles of HbA1c, and by HbA1c continuously at Cox regression, with covariance adjustment for age, sex, diabetes duration, smoking and insulin treatment, or adjusting with a propensity score. Results: Comparing HbA1c &gt;58 mmol/mol with &lt;= 58 mmol/mol, adjusted HR for all cancer was 1.02 [95% CI 0.95-1.10] using baseline HbA1c, and 1.04 [95% CI 0.97-1.12] using updated mean HbA1c, and HRs were all non-significant for specific cancers of gastrointestinal, kidney and urinary organs, respiratory organs, female genital organs, breast or prostate. Similarly, no increased risks of all cancer or the specific types of cancer were found with higher quartiles of baseline or updated mean HbA1c, compared to the lowest quartile. HR for all cancer was 1.01 [0.98-1.04] per 1%-unit increase in HbA1c used as a continuous variable, with non-significant HRs also for the specific types of cancer per unit increase in HbA1c. Conclusions: In this study there were no associations between HbA1c and risks for all cancers or specific types of cancer in patients with type 2 diabetes

Resolution-of-identity approach to Hartree-Fock, hybrid density functionals, RPA, MP2, and \textit{GW} with numeric atom-centered orbital basis functions

Efficient implementations of electronic structure methods are essential for first-principles modeling of molecules and solids. We here present a particularly efficient common framework for methods beyond semilocal density-functional theory, including Hartree-Fock (HF), hybrid density functionals, random-phase approximation (RPA), second-order M{\o}ller-Plesset perturbation theory (MP2), and the $GW$ method. This computational framework allows us to use compact and accurate numeric atom-centered orbitals (popular in many implementations of semilocal density-functional theory) as basis functions. The essence of our framework is to employ the "resolution of identity (RI)" technique to facilitate the treatment of both the two-electron Coulomb repulsion integrals (required in all these approaches) as well as the linear density-response function (required for RPA and $GW$). This is possible because these quantities can be expressed in terms of products of single-particle basis functions, which can in turn be expanded in a set of auxiliary basis functions (ABFs). The construction of ABFs lies at the heart of the RI technique, and here we propose a simple prescription for constructing the ABFs which can be applied regardless of whether the underlying radial functions have a specific analytical shape (e.g., Gaussian) or are numerically tabulated. We demonstrate the accuracy of our RI implementation for Gaussian and NAO basis functions, as well as the convergence behavior of our NAO basis sets for the above-mentioned methods. Benchmark results are presented for the ionization energies of 50 selected atoms and molecules from the G2 ion test set as obtained with $GW$ and MP2 self-energy methods, and the G2-I atomization energies as well as the S22 molecular interaction energies as obtained with the RPA method.Comment: 58 pages, 15 figures, and 7 table

Predictors of Long-Term Care Utilization by Dutch Hospital Patients aged 65+

Background Long-term care is often associated with high health care expenditures. In the Netherlands, an ageing population will likely increase the demand for long-term care within the near future. The development of risk profiles will not only be useful for projecting future demand, but also for providing clues that may prevent or delay long-term care utilization. Here, we report our identification of predictors of long-term care utilization in a cohort of hospital patients aged 65+ following their discharge from hospital discharge and who, prior to hospital admission, were living at home. Methods The data were obtained from three national databases in the Netherlands: the national hospital discharge register, the long-term care expenses register and the population register. Multinomial logistic regression was applied to determine which variables were the best predictors of long-term care utilization. The model included demographic characteristics and several medical diagnoses. The outcome variables were discharge to home with no formal care (reference category), discharge to home with home care, admission to a nursing home and admission to a home for the elderly. Results The study cohort consisted of 262,439 hospitalized patients. A higher age, longer stay in the hospital and absence of

ACC2 Is Expressed at High Levels Human White Adipose and Has an Isoform with a Novel N-Terminus

Acetyl-CoA carboxylases ACC1 and ACC2 catalyze the carboxylation of acetyl-CoA to malonyl-CoA, regulating fatty-acid synthesis and oxidation, and are potential targets for treatment of metabolic syndrome. Expression of ACC1 in rodent lipogenic tissues and ACC2 in rodent oxidative tissues, coupled with the predicted localization of ACC2 to the mitochondrial membrane, have suggested separate functional roles for ACC1 in lipogenesis and ACC2 in fatty acid oxidation. We find, however, that human adipose tissue, unlike rodent adipose, expresses more ACC2 mRNA relative to the oxidative tissues muscle and heart. Human adipose, along with human liver, expresses more ACC2 than ACC1. Using RT-PCR, real-time PCR, and immunoprecipitation we report a novel isoform of ACC2 (ACC2.v2) that is expressed at significant levels in human adipose. The protein generated by this isoform has enzymatic activity, is endogenously expressed in adipose, and lacks the N-terminal sequence. Both ACC2 isoforms are capable of de novo lipogenesis, suggesting that ACC2, in addition to ACC1, may play a role in lipogenesis. The results demonstrate a significant difference in ACC expression between human and rodents, which may introduce difficulties for the use of rodent models for development of ACC inhibitors

Stable carbon and nitrogen isotope enrichment in primate tissues

Isotopic studies of wild primates have used a wide range of tissues to infer diet and model the foraging ecologies of extinct species. The use of mismatched tissues for such comparisons can be problematic because differences in amino acid compositions can lead to small isotopic differences between tissues. Additionally, physiological and dietary differences among primate species could lead to variable offsets between apatite carbonate and collagen. To improve our understanding of the isotopic chemistry of primates, we explored the apparent enrichment (ε*) between bone collagen and muscle, collagen and fur or hair keratin, muscle and keratin, and collagen and bone carbonate across the primate order. We found that the mean ε* values of proteinaceous tissues were small (≤1‰), and uncorrelated with body size or phylogenetic relatedness. Additionally, ε* values did not vary by habitat, sex, age, or manner of death. The mean ε* value between bone carbonate and collagen (5.6 ± 1.2‰) was consistent with values reported for omnivorous mammals consuming monoisotopic diets. These primate-specific apparent enrichment values will be a valuable tool for cross-species comparisons. Additionally, they will facilitate dietary comparisons between living and fossil primates

A predictive model for the early identification of patients at risk for a prolonged intensive care unit length of stay

<p>Abstract</p> <p>Background</p> <p>Patients with a prolonged intensive care unit (ICU) length of stay account for a disproportionate amount of resource use. Early identification of patients at risk for a prolonged length of stay can lead to quality enhancements that reduce ICU stay. This study developed and validated a model that identifies patients at risk for a prolonged ICU stay.</p> <p>Methods</p> <p>We performed a retrospective cohort study of 343,555 admissions to 83 ICUs in 31 U.S. hospitals from 2002-2007. We examined the distribution of ICU length of stay to identify a threshold where clinicians might be concerned about a prolonged stay; this resulted in choosing a 5-day cut-point. From patients remaining in the ICU on day 5 we developed a multivariable regression model that predicted remaining ICU stay. Predictor variables included information gathered at admission, day 1, and ICU day 5. Data from 12,640 admissions during 2002-2005 were used to develop the model, and the remaining 12,904 admissions to internally validate the model. Finally, we used data on 11,903 admissions during 2006-2007 to externally validate the model.</p> <p>Results</p> <p>The variables that had the greatest impact on remaining ICU length of stay were those measured on day 5, not at admission or during day 1. Mechanical ventilation, PaO₂: FiO₂ratio, other physiologic components, and sedation on day 5 accounted for 81.6% of the variation in predicted remaining ICU stay. In the external validation set observed ICU stay was 11.99 days and predicted total ICU stay (5 days + day 5 predicted remaining stay) was 11.62 days, a difference of 8.7 hours. For the same patients, the difference between mean observed and mean predicted ICU stay using the APACHE day 1 model was 149.3 hours. The new model's r²was 20.2% across individuals and 44.3% across units.</p> <p>Conclusions</p> <p>A model that uses patient data from ICU days 1 and 5 accurately predicts a prolonged ICU stay. These predictions are more accurate than those based on ICU day 1 data alone. The model can be used to benchmark ICU performance and to alert physicians to explore care alternatives aimed at reducing ICU stay.</p