The Cluster Mass Function from Early SDSS Data: Cosmological Implications

The mass function of clusters of galaxies is determined from 400 deg^2 of early commissioning imaging data of the Sloan Digital Sky Survey; ~300 clusters in the redshift range z = 0.1 - 0.2 are used. Clusters are selected using two independent selection methods: a Matched Filter and a red-sequence color magnitude technique. The two methods yield consistent results. The cluster mass function is compared with large-scale cosmological simulations. We find a best-fit cluster normalization relation of sigma_8*omega_m^0.6 = 0.33 +- 0.03 (for 0.1 ~< omega_m ~< 0.4), or equivalently sigma_8 = (0.16/omega_m)^0.6. The amplitude of this relation is significantly lower than the previous canonical value, implying that either omega_m is lower than previously expected (omega_m = 0.16 if sigma_8 = 1) or sigma_8 is lower than expected (sigma_8 = 0.7 if omega_m = 0.3). The best-fit mass function parameters are omega_m = 0.19 (+0.08,-0.07) and sigma_8 = 0.9 (+0.3,-0.2). High values of omega_m (>= 0.4) and low sigma_8 (=~ 2 sigma.Comment: AASTeX, 25 pages, including 7 figures, accepted for publication in ApJ, vol.585, March 200

A Merged Catalog of Clusters of Galaxies from Early SDSS Data

We present a catalog of 799 clusters of galaxies in the redshift range z_est = 0.05 - 0.3 selected from ~400 deg^2 of early SDSS commissioning data along the celestial equator. The catalog is based on merging two independent selection methods -- a color-magnitude red-sequence maxBCG technique (B), and a Hybrid Matched-Filter method (H). The BH catalog includes clusters with richness \Lambda >= 40 (Matched-Filter) and N_gal >= 13 (maxBCG), corresponding to typical velocity dispersion of \sigma_v >~ 400 km s^{-1} and mass (within 0.6 h^{-1) Mpc radius) >~ 5*10^{13} h^{-1} M_sun. This threshold is below Abell richness class 0 clusters. The average space density of these clusters is 2*10^{-5} h^3 Mpc^{-3}. All NORAS X-ray clusters and 53 of the 58 Abell clusters in the survey region are detected in the catalog; the 5 additional Abell clusters are detected below the BH catalog cuts. The cluster richness function is determined and found to exhibit a steeply decreasing cluster abundance with increasing richness. We derive observational scaling relations between cluster richness and observed cluster luminosity and cluster velocity dispersion; these scaling relations provide important physical calibrations for the clusters. The catalog can be used for studies of individual clusters, for comparisons with other sources such as X-ray clusters and AGNs, and, with proper correction for the relevant selection functions, also for statistical analyses of clusters.Comment: AASTeX, 62 pages, including 14 figures and 4 tables, submitted to ApJS. Paper with full-resolution figures at http://astro.princeton.edu/~feng/sdss_cluster.p

The impact of multimorbidity on adult physical and mental health in low- and middle-income countries: what does the study on global ageing and adult health (SAGE) reveal?

BACKGROUND: Chronic diseases contribute a large share of disease burden in low- and middle-income countries (LMICs). Chronic diseases have a tendency to occur simultaneously and where there are two or more such conditions, this is termed as 'multimorbidity'. Multimorbidity is associated with adverse health outcomes, but limited research has been undertaken in LMICs. Therefore, this study examines the prevalence and correlates of multimorbidity as well as the associations between multimorbidity and self-rated health, activities of daily living (ADLs), quality of life, and depression across six LMICs. METHODS: Data was obtained from the WHO's Study on global AGEing and adult health (SAGE) Wave-1 (2007/10). This was a cross-sectional population based survey performed in LMICs, namely China, Ghana, India, Mexico, Russia, and South Africa, including 42,236 adults aged 18 years and older. Multimorbidity was measured as the simultaneous presence of two or more of eight chronic conditions including angina pectoris, arthritis, asthma, chronic lung disease, diabetes mellitus, hypertension, stroke, and vision impairment. Associations with four health outcomes were examined, namely ADL limitation, self-rated health, depression, and a quality of life index. Random-intercept multilevel regression models were used on pooled data from the six countries. RESULTS: The prevalence of morbidity and multimorbidity was 54.2 % and 21.9 %, respectively, in the pooled sample of six countries. Russia had the highest prevalence of multimorbidity (34.7 %) whereas China had the lowest (20.3 %). The likelihood of multimorbidity was higher in older age groups and was lower in those with higher socioeconomic status. In the pooled sample, the prevalence of 1+ ADL limitation was 14 %, depression 5.7 %, self-rated poor health 11.6 %, and mean quality of life score was 54.4. Substantial cross-country variations were seen in the four health outcome measures. The prevalence of 1+ ADL limitation, poor self-rated health, and depression increased whereas quality of life declined markedly with an increase in number of diseases. CONCLUSIONS: Findings highlight the challenge of multimorbidity in LMICs, particularly among the lower socioeconomic groups, and the pressing need for reorientation of health care resources considering the distribution of multimorbidity and its adverse effect on health outcomes

Measuring the predictability of life outcomes with a scientific mass collaboration.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P &lt; 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Effect of remote ischaemic conditioning on clinical outcomes in patients with acute myocardial infarction (CONDI-2/ERIC-PPCI): a single-blind randomised controlled trial.

BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden

Reduction in meridional heat export contributes to recent Indian Ocean warming

Since 2000, the Indian Ocean has warmed more rapidly than the Atlantic or Pacific Oceans. Air–sea fluxes alone cannot explain the rapid Indian Ocean warming, which has so far been linked to an increase in temperature transport into the basin through the Indonesian Throughflow (ITF). Here, we investigate the role that the heat transport out of the basin at 36°S plays in the warming. Adding the heat transport out of the basin to the ITF temperature transport into the basin, we calculate the decadal mean Indian Ocean heat budget over the 2010s. We find that heat convergence increased within the Indian Ocean over 2000–19. The heat convergence over the 2010s is of the same order as the warming rate, and thus the net air–sea fluxes are near zero. This is a significant change from previous analyses using transbasin hydrographic sections from 1987, 2002, and 2009, which all found divergences of heat. A 2-yr time series shows that seasonal aliasing is not responsible for the decadal change. The anomalous ocean heat convergence over the 2010s in comparison with previous estimates is due to changes in ocean currents at both the southern boundary (33%) and the ITF (67%). We hypothesize that the changes at the southern boundary are linked to an observed broadening of the Agulhas Current, implying that temperature and velocity data at the western boundary are crucial to constrain heat budget changes

Reduction in meridional heat export contributes to recent Indian Ocean warming

Since 2000, the Indian Ocean has warmed more rapidly than the Atlantic or Pacific. Air-sea fluxes alone cannot explain the rapid Indian Ocean warming, which has so far been linked to an increase in temperature transport into the basin through the Indonesian Throughflow (ITF). Here, we investigate the role that the heat transport out of the basin at 36°S plays in the warming. Adding the heat transport out of the basin to the ITF temperature transport into the basin, we calculate the decadal mean Indian Ocean heat budget over the 2010s. We find that heat convergence increased within the Indian Ocean over 2000-2019. The heat convergence over the 2010s is the same order as the warming rate, and thus the net air-sea fluxes are near zero. This is a significant change from previous analyses using trans-basin hydrographic sections from 1987, 2002, and 2009, which all found divergences of heat. A two year time series shows that seasonal aliasing is not responsible for the decadal change. The anomalous ocean heat convergence over the 2010s compared to previous estimates is due to changes in ocean currents at both the southern boundary (33%) and the ITF (67%). We hypothesize that the changes at the southern boundary are linked to an observed broadening of the Agulhas Current, implying that temperature and velocity data at the western boundary are crucial to constrain heat budget changes

Insurance and the Natural Assurance Value (of Ecosystems) in Risk Prevention and Reduction

International audienceClimate change is increasing the frequency and intensity of natural disasters and can threaten the functions of ecosystems. Affected, damaged or destroyed ecosystems in turn also make our societies more vulnerable to natural hazards and climate change (i.e. their assurance value). In addition, expanding communities and concentrations of wealth in high-risk areas are increasing risk exposure dramatically. This chapter outlines the growing interest in the protective role nature-based solutions (NBS) can play in buffering against risks posed by natural hazards. It presents mechanisms and potential roles of the insurance industry to facilitate loss prevention through NBS. The use of catastrophe models to quantify the assurance value of nature (in line with Chaps. 1 and 2 ), the benefits of nature in reducing natural hazards-related damages have been highlighted. Catastrophe models developed and run by insurance companies are well-suited to support the quantification of the avoided damage provided by NBS. This can be performed in complement to research institutions assessments of co-benefits NBS provide (as outlined in the case studies’ chapters). The findings developed in this chapter make a strong case for pro-active engagement of the insurance industry in assessing nature-based risk reduction measures and public/private plans for implementation and monitoring. Graphical Abstrac