Use of antipsychotic medication and its relationship with bone mineral density: A population-based study of men and women

BackgroundSchizophrenia has been shown to be associated with reduced bone mineral density (BMD) and higher fracture risk. However, less is known whether antipsychotic treatment is associated with reduced BMD. Thus, we aimed to examine associations between antipsychotic use and BMD among men and women drawn from the general population.MethodsThis cross-sectional study involved 793 women and 587 men enrolled in the Geelong Osteoporosis Study (GOS). BMD was determined using dual-energy X-ray absorptiometry at the spine and hip. Information regarding socio-economic status (SES), current medication and/or supplementation use, lifestyle factors, and anthropometry was collected. Association between antipsychotic use and BMD was determined using linear regression after adjusting for potential confounders.ResultsOf the group, 33 women (4.2%) and 16 men (2.7%) currently used antipsychotics. Age was identified as an effect modifier in the association between antipsychotic use and BMD for women. Amongst women aged < 60 years, adjusted mean BMD was 11.1% lower at the spine [1.139 (95%CI 1.063–1.216) vs. 1.250 (95%CI 1.223–1.277) g/cm2, p = 0.005] for antipsychotic users compared to non-users. At the hip, age, weight, and smoking adjusted mean BMD was 9.9% lower [0.893 (95%CI 0.837–0.950) vs. 0.992 (95%CI 0.976–1.007) g/cm2, p < 0.001] for antipsychotic users in comparison with non-users. The pattern persisted following further adjustments. There was no association detected between antipsychotic use and BMD for women aged 60 years and over and for men.ConclusionOur data suggest that antipsychotic medication use is associated with reduced BMD in younger women but not older women or men

Change in weight and waist circumference and risk of colorectal cancer: Results from the Melbourne Collaborative Cohort Study

Background: Studies reporting the association between change in weight or body mass index during midlife and risk of colorectal cancer have found inconsistent results, and only one study to date has reported the association between change in waist circumference (a measure of central adiposity) and risk of colorectal cancer. Methods: We investigated the association between risk of colorectal cancer and changes in directly measured waist circumference and weight from baseline (1990-1994) to wave 2 (2003-2007). Cox regression, with age as the time metric and follow-up starting at wave 2, adjusted for covariates selected from a causal model, was used to estimate the Hazard Ratios (HRs) and 95 % Confidence Intervals (CIs) for the change in waist circumference and weight in relation to risk of colorectal cancer. Results: A total of 373 cases of colorectal cancer were diagnosed during an average 9 years of follow-up of 20,605 participants. Increases in waist circumference and weight were not associated with the risk of colorectal cancer (HR per 5 cm increase in waist circumference = 1.02; 95 % CI: 0.95, 1.10; HR per 5 kg increase in weight = 0.93; 0.85, 1.02). For individuals with a waist circumference at baseline that was less than the sex-specific mean value there was a slight increased risk of colorectal cancer associated with a 5 cm increase in waist circumference at wave 2 (HR = 1.08; 0.97, 1.21). Conclusion: Increases in waist circumference and weight during midlife do not appear to be associated with the risk of colorectal cancer

Sustained adherence to a Mediterranean diet and physical activity on all-cause mortality in the Melbourne Collaborative Cohort Study: application of the g-formula.

BACKGROUND: Adherence to a traditional Mediterranean diet has been associated with lower mortality and cardiovascular disease risk. The relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time remains unknown. METHODS: We used the parametric G-formula to account for time-dependent confounding, in order to assess the relative importance of diet compared to other lifestyle factors and effects of dietary patterns over time. We included healthy Melbourne Collaborative Cohort Study participants attending a visit during 1995-1999. Questionnaires assessed diet and physical activity at each of three study waves. Deaths were identified by linkage to national registries. We estimated mortality risk over approximately 14 years (1995-2011). RESULTS: Of 22,213 participants, 2163 (9.7%) died during 13.6 years median follow-up. Sustained high physical activity and adherence to a Mediterranean-style diet resulted in an estimated reduction in all-cause mortality of 1.82 per 100 people (95% confidence interval (CI): 0.03, 3.6). The population attributable fraction was 13% (95% CI: 4, 23%) for sustained high physical activity, 7% (95% CI: - 3, 17%) for sustained adherence to a Mediterranean-style diet and 18% (95% CI: 0, 36%) for their combination. CONCLUSIONS: A small reduction in mortality may be achieved by sustained elevated physical activity levels in healthy middle-aged adults, but there may be comparatively little gain from increasing adherence to a Mediterranean-style diet

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Helen Walker - More Apt, Connected Title Sheryl Lain - Hey, Teach! Do You Love Me? Matthew B. Ittig - Ask Me Tomorrow Laurence Musgrove - Writing Program Julie O’Connell - The Power of a Slave Narrative Leslie A. Werden - Embracing Chaos Donna Souder-Hodge - Teaching Dachau Tanya R. Cochran, Rasha Diab, Thomas Ferrel, & Beth Godbee - Hanging Out: Cultivating Life-Giving Writing Groups Onlin

Detection of a Thermal Spectral Component in the Prompt Emission of GRB 100724B

Observations of GRB 100724B with the Fermi Gamma-Ray Burst Monitor (GBM) find that the spectrum is dominated by the typical Band functional form, which is usually taken to represent a non-thermal emission component, but also includes a statistically highly significant thermal spectral contribution. The simultaneous observation of the thermal and non-thermal components allows us to confidently identify the two emission components. The fact that these seem to vary independently favors the idea that the thermal component is of photospheric origin while the dominant non-thermal emission occurs at larger radii. Our results imply either a very high efficiency for the non-thermal process, or a very small size of the region at the base of the flow, both quite challenging for the standard fireball model. These problems are resolved if the jet is initially highly magnetized and has a substantial Poynting flux.Comment: 6 pages, 3 figures, 1 table, Accepted for publication in the Astrophysical Journal Letters November, 23 2010 (Submitted October, 20 2010

Association between bipolar spectrum disorder and bone health: a meta-analysis and systematic review protocol

Introduction Bipolar spectrum disorder is a chronic, episodic illness, associated with significant personal, social and economic burden. It is estimated to affect ∼2.4% of the population worldwide and is commonly associated with psychological and/or physiological comorbidities. Osteoporosis is one such comorbidity, a disease of bone that is asymptomatic until a fracture occurs. This systematic review attempts to capture, collate, assess and discuss the literature investigating the association between bipolar spectrum disorder and bone health.Methods and analysis We aim to identify articles that investigate the association between bipolar spectrum disorder and bone health in adults by systematically searching the MEDLINE, PubMed, OVID and CINAHL databases. Two independent reviewers will determine eligibility of studies according to predetermined criteria, and methodological quality will be assessed using a previously published scoring system. A meta-analysis will be conducted, and statistical methods will be used to identify and control for heterogeneity, if possible. If numerical syntheses are prevented due to statistical heterogeneity, a best evidence synthesis will be conducted to assess the level of evidence for associations between bipolar spectrum disorder and bone health

Constraining the Lyα escape fraction with far-infrared observations of Lyα emitters

We study the far-infrared properties of 498 Lyα emitters (LAEs) at z = 2.8, 3.1, and 4.5 in the Extended Chandra Deep Field-South, using 250, 350, and 500μm data from the Herschel Multi-tiered Extragalactic Survey and 870μm data from the LABOCA ECDFS Submillimeter Survey. None of the 126, 280, or 92 LAEs at z = 2.8, 3.1, and 4.5, respectively, are individually detected in the far-infrared data. We use stacking to probe the average emission to deeper flux limits, reaching 1σ depths of ∼0.1 to 0.4 mJy. The LAEs are also undetected at ?3σ in the stacks, although a 2.5σ signal is observed at 870μm for the z = 2.8 sources. We consider a wide range of far-infrared spectral energy distributions (SEDs), including an M82 and an Sd galaxy template, to determine upper limits on the far-infrared luminosities and far-infrared-derived star formation rates of the LAEs. These star formation rates are then combined with those inferred from the Lyα and UV emission to determine lower limits on the LAEs’ Lyα escape fraction (f esc (Lyα)). For the Sd SED template, the inferred LAEs f esc (Lyα) are ?30% (1σ) at z = 2.8, 3.1, and 4.5, which are all significantly higher than the global f esc (Lyα) at these redshifts. Thus, if the LAEs f esc (Lyα) follows the global evolution, then they have warmer far-infrared SEDs than the Sd galaxy template. The average and M82 SEDs produce lower limits on the LAE f esc (Lyα) of ∼10%–20% (1σ), all of which are slightly higher than the global evolution of f esc (Lyα), but consistent with it at the 2σ–3σ level

Prevalence of Obesity and the Relationship between the Body Mass Index and Body Fat: Cross-Sectional, Population-Based Data

Background: Anthropometric measures such as the body mass index (BMI) and waist circumference are widely used as convenient indices of adiposity, yet there are limitations in their estimates of body fat. We aimed to determine the prevalence of obesity using criteria based on the BMI and waist circumference, and to examine the relationship between the BMI and body fat.Methodology/Principal Findings: This population-based, cross-sectional study was conducted as part of the Geelong Osteoporosis Study. A random sample of 1,467 men and 1,076 women aged 20&ndash;96 years was assessed 2001&ndash;2008. Overweight and obesity were identified according to BMI (overweight 25.0&ndash;29.9 kg/m2; obesity 30.0 kg/m2) and waist circumference (overweight men 94.0–101.9 cm; women 80.0–87.9 cm; obesity men 102.0 cm, women $88.0 cm); body fat mass was assessed using dual energy X-ray absorptiometry; height and weight were measured and lifestyle factors documented by self-report. According to the BMI, 45.1% (95%CI 42.4&ndash;47.9) of men and 30.2% (95%CI 27.4&ndash;33.0) of women were overweight and a further 20.2% (95%CI 18.0&ndash;22.4) of men and 28.6% (95%CI 25.8&ndash;31.3) of women were obese. Using waist circumference, 27.5% (95%CI 25.1&ndash;30.0) of men and 23.3% (95%CI 20.8&ndash;25.9) of women were overweight, and 29.3% (95%CI 26.9&ndash;31.7) of men and 44.1% (95%CI 41.2&ndash;47.1) of women, obese. Both criteria indicate that approximately 60% of the population exceeded recommended thresholds for healthy body habitus. There was no consistent pattern apparent between BMI and energy intake. Compared with women, BMI overestimated adiposity in men, whose excess weight was largely attributable to muscular body builds and greater bone mass. BMI also underestimated adiposity in the elderly. Regression models including gender, age and BMI explained 0.825 of the variance in percent body fat.Conclusions/Significance: As the BMI does not account for differences in body composition, we suggest that gender- and age-specific thresholds should be considered when the BMI is used to indicate adiposity.<br /

Comparing different definitions of prediabetes with subsequent risk of diabetes: an individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes

Objective: There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful. Research design and methods: We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points. Results: Sixteen studies, with 76 513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1 mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6 mmol/L, 2-hour postload glucose 7.0 mmol/L and HbA1c 5.6% (38 mmol/mol). Conclusions: In terms of identifying individuals at greatest risk of developing diabetes within 5 years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.This work was supported by the National Health and Medical Research Council of Australia (grant number 1103242). The Atherosclerosis Risk in Communities study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under contract nos. HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I. ES was supported by NIH/NIDDK grant K24DK106414. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN2682018000031, HHSN2682018000041, HHSN2682018000051, HHSN2682018000061 and HHSN2682018000071 from the National Heart, Lung, and Blood Institute (NHLBI). The Jackson Heart Study (JHS) is supported and conducted in collaboration with Jackson State University (HHSN268201800013I), Tougaloo College (HHSN268201800014I), the Mississippi State Department of Health (HHSN268201800015I) and the University of Mississippi Medical Center (HHSN268201800010I, HHSN268201800011I and HHSN268201800012I) contracts from the National Heart, Lung, and Blood Institute (NHLBI) and the National Institute for Minority Health and Health Disparities (NIMHD). The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further augmented by Australian National Health and Medical Research Council grants 209057, 396414 and 1074383 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The Multi-Ethnic Study of Atherosclerosis was supported by contracts HHSN268201500003I, N01-HC-95159, N01-HC-95160, N01-HC-95161, N01-HC-95162, N01-HC-95163, N01-HC-95164, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168 and N01-HC-95169 from the National Heart, Lung, and Blood Institute and by grants UL1-TR-000040 and UL1-TR-001079 from NCRR. The Population Study of Women in Gothenburg (PSWG) was financed in part by grants from the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement ALFGBG-720201. VIVA Study received grants 95/0029 and 06/90270 from the Instituto de Salud Carlos III, Spain.S