Estimates of Private Sector Wealth

This paper provides quarterly estimates of private non-human wealth at market prices in Australia over the past decade. These estimates are based on the methodology set out in Piggott (1987), although improvements have been made in several important areas. The estimates suggest that private non-human wealth stood at $1,428 billion in the June quarter 1990. The dwelling stock accounted for 52 per cent of the total, business assets for 37 per cent, with the remainder being made up of consumer durables, holdings of government bonds and holdings of currency. The paper also introduces an index of asset prices, based on the wealth estimates.

Smoking cessation for people with severe mental illness (SCIMITAR+) : a pragmatic randomised controlled trial

BACKGROUND: People with severe mental illnesses such as schizophrenia are three times more likely to smoke than the wider population, contributing to widening health inequalities. Smoking remains the largest modifiable risk factor for this health inequality, but people with severe mental illness have not historically engaged with smoking cessation services. We aimed to test the effectiveness of a combined behavioural and pharmacological smoking cessation intervention targeted specifically at people with severe mental illness. METHODS: In the smoking cessation intervention for severe mental illness (SCIMITAR+) trial, a pragmatic, randomised controlled study, we recruited heavy smokers with bipolar disorder or schizophrenia from 16 primary care and 21 community-based mental health sites in the UK. Participants were eligible if they were aged 18 years or older, and smoked at least five cigarettes per day. Exclusion criteria included substantial comorbid drug or alcohol problems and people who lacked capacity to consent at the time of recruitment. Using computer-generated random numbers, participants were randomly assigned (1:1) to a bespoke smoking cessation intervention or to usual care. Participants, mental health specialists, and primary care physicians were unmasked to assignment. The bespoke smoking cessation intervention consisted of behavioural support from a mental health smoking cessation practitioner and pharmacological aids for smoking cessation, with adaptations for people with severe mental illness-such as, extended pre-quit sessions, cut down to quit, and home visits. Access to pharmacotherapy was via primary care after discussion with the smoking cessation specialist. Under usual care participants were offered access to local smoking cessation services not specifically designed for people with severe mental illnesses. The primary endpoint was smoking cessation at 12 months ascertained via carbon monoxide measurements below 10 parts per million and self-reported cessation for the past 7 days. Secondary endpoints were biologically verified smoking cessation at 6 months; number of cigarettes smoked per day, Fagerström Test for Nicotine Dependence (FTND) and Motivation to Quit (MTQ) questionnaire; general and mental health functioning determined via the Patient Health Questionnaire-9 (PHQ-9), the Generalised Anxiety Disorder-7 (GAD-7) questionnaire, and 12-Item Short Form Health Survey (SF-12); and body-mass index (BMI). This trial was registerd with the ISRCTN registry, number ISRCTN72955454, and is complete. FINDINGS: Between Oct 7, 2015, and Dec 16, 2016, 526 eligible patients were randomly assigned to the bespoke smoking cessation intervention (n=265) or usual care (n=261). 309 (59%) participants were male, median age was 47·2 years (IQR 36·3-54·5), with high nicotine dependence (mean 24 cigarettes per day [SD 13·2]), and the most common severe mental disorders were schizophrenia or other psychotic illness (n=343 [65%]), bipolar disorder (n=115 [22%]), and schizoaffective disorder (n=66 [13%]). 234 (88%) of intervention participants engaged with the treatment programme and attended 6·4 (SD 3·5) quit smoking sessions, with an average duration of 39 min (SD 17; median 35 min, range 5-120). Verified quit data at 12 months were available for 219 (84%) of 261 usual care and 223 (84%) of 265 intervention participants. The proportion of participants who had quit at 12 months was higher in the intervention group than in the usual care group, but non-significantly (34 [15%] of 223 [13% of those assigned to group] vs 22 [10%] of 219 [8% of those assigned to group], risk difference 5·2%, 95% CI -1·0 to 11·4; odds ratio [OR] 1·6, 95% CI 0·9 to 2·9; p=0·10). The proportion of participants who quit at 6 months was significantly higher in the intervention group than in the usual care group (32 [14%] of 226 vs 14 [6%] of 217; risk difference 7·7%, 95% CI 2·1 to 13·3; OR 2·4, 95% CI 1·2 to 4·6; p=0·010). The incidence rate ratio for number of cigarettes smoked per day at 6 months was 0·90 (95% CI 0·80 to 1·01; p=0·079), and at 12 months was 1·00 (0·89 to 1·13; p=0·95). At both 6 months and 12 months, the intervention group was non-significantly favoured in the FTND (adjusted mean difference 6 months -0·18, 95% CI -0·53 to 0·17, p=0·32; and 12 months -0·01, -0·39 to 0·38, p=0·97) and MTQ questionnaire (adjusted mean difference 0·58, -0·01 to 1·17, p=0·056; and 12 months 0·64, 0·04 to 1·24, p=0·038). The PHQ-9 showed no difference between the groups (adjusted mean difference at 6 months 0·20, 95% CI -0·85 to 1·24 vs 12 months -0·12, -1·18 to 0·94). For the SF-12 survey, we saw evidence of improvement in physical health in the intervention group at 6 months (adjusted mean difference 1·75, 95% CI 0·21 to 3·28), but this difference was not evident at 12 months (0·59, -1·07 to 2·26); and we saw no difference in mental health between the groups at 6 or 12 months (adjusted mean difference at 6 months -0·73, 95% CI -2·82 to 1·36, and 12 months -0·41, -2·35 to 1·53). The GAD-7 questionnaire showed no difference between the groups (adjusted mean difference at 6 months -0·32 95% CI -1·26 to 0·62 vs 12 months -0·10, -1·05 to 0·86). No difference in BMI was seen between the groups (adjusted mean difference 6 months 0·16, 95% CI -0·54 to 0·85; 12 months 0·25, -0·62 to 1·13). INTERPRETATION: This bespoke intervention is a candidate model of smoking cessation for clinicians and policy makers to address high prevalence of smoking. The incidence of quitting at 6 months shows that smoking cessation can be achieved, but the waning of this effect by 12 months means more effort is needed for sustained quitting. FUNDING: National Institute for Health Research Health Technology Assessment Programme

Global inequities and emissions in Western European textiles and clothing consumption

YesRising demand for cheaper textiles and clothing in Western Europe is well documented, as are changes in the Textiles and Clothing industry's globalised production structure. We apply a sub-systems global multi-regional input–output accounting framework to examine the sustainability implications of meeting Western European demand for textiles and clothing goods between 1995 and 2009. Our framework estimates environmental and socio-economic impacts of consumption in a consistent manner and shows where these occur both geographically and in the value chain. The results demonstrate that Western European textiles and clothing consumption remains dependent on low-cost labour from Brazil, Russia, India and China (BRIC), principally in the Textiles and Clothing and Agricultural sectors. Conversely, we show that the wage rate for BRIC workers in the global value chains serving Western European textiles and clothing consumption has risen over time but remains low relative to the wage rate paid to Western European workers. Likewise, we find that profits are increasingly generated within BRIC and that they are now at comparable levels to those generated in Western Europe. We find a slight overall decrease in the amount of carbon emitted in the production of textiles and clothing goods for Western Europe between 1995 and 2009. However, the trend is not linear and the importance of different underlying drivers varies over the timeseries. We conclude by discussing the implications of these results for a more sustainable future for Western European textiles and clothing consumption

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Empirical Determinants of Household Saving

This paper analyzes the empirical determinants of household saving using data from 21 OECD countries for 1975-95. A particular focus is the influence of the tax and social security systems on household saving. The paper therefore extends the usual set of explanatory variables used to explain household saving behavior to include variables that capture the structure of the tax system and the financing and generosity of the social security and welfare system. These variables are found to have an important impact on household saving. Accordingly, by changing the design of these systems, governments may be able to influence saving.

Modeling and Forecasting Inflation in India

The Reserve Bank of India (RBI) has moved away from a broad money target toward a “multiple indicators” approach to the conduct of monetary policy. In adopting such a framework, it is necessary to know which of the many potential indicators provide the most reliable and timely information on future developments in the target variable(s). This paper assesses which indicators provide the most useful information about future inflationary trends. It concludes that while the broad money target has been de-emphasized, developments in the monetary aggregates remain an important indicator of future inflation. The exchange rate and import prices are also relevant, particularly for inflation in the manufacturing sector.