Mapping the Dark Matter From UV Light at High Redshift: An Empirical Approach to Understand Galaxy Statistics

We present a simple formalism to interpret two galaxy statistics, the UV luminosity function and two-point correlation functions for star-forming galaxies at z~4, 5, 6 in the context of LCDM cosmology. Both statistics are the result of how star formation takes place in DM halos, and thus are used to constrain how UV light depends on halo properties such as mass. The two measures were taken from the GOODS data, thus ideal for joint analysis. The two physical quantities we explore are the SF duty cycle, and the range of L_UV that a halo of mass M can have (mean and variance). The former addresses the typical duration of SF activity in halos while the latter addresses the averaged SF history and regularity of gas inflow into these systems. We explore various physical models consistent with data, and find the following: 1) the typical duration of SF observed in the data is <0.4 Gyr (1 sig), 2) the inferred scaling law between L_UV and halo mass M from the observed slope of the LFs is roughly linear at all redshifts, and 3) L_UV for a fixed halo mass decreases with time, implying that the SF efficiency (after dust extinction) is higher at earlier times. We explore several physical scenarios relating star formation to halo mass, but find that these scenarios are indistinguishable due to the limited range of halo mass probed by our data. In order to discriminate between different scenarios, we discuss constraining the bright-faint galaxy cross-correlation functions and luminosity-dependence of galaxy bias. (Abridged)Comment: 24 pages, 16 figures: matches published version -- Astrophysical Journal 695 (2009) 368-39

The Average Star Formation Histories of Galaxies in Dark Matter Halos from z=0-8

We present a robust method to constrain average galaxy star formation rates, star formation histories, and the intracluster light as a function of halo mass. Our results are consistent with observed galaxy stellar mass functions, specific star formation rates, and cosmic star formation rates from z=0 to z=8. We consider the effects of a wide range of uncertainties on our results, including those affecting stellar masses, star formation rates, and the halo mass function at the heart of our analysis. As they are relevant to our method, we also present new calibrations of the dark matter halo mass function, halo mass accretion histories, and halo-subhalo merger rates out to z=8. We also provide new compilations of cosmic and specific star formation rates; more recent measurements are now consistent with the buildup of the cosmic stellar mass density at all redshifts. Implications of our work include: halos near 10^12 Msun are the most efficient at forming stars at all redshifts, the baryon conversion efficiency of massive halos drops markedly after z ~ 2.5 (consistent with theories of cold-mode accretion), the ICL for massive galaxies is expected to be significant out to at least z ~ 1-1.5, and dwarf galaxies at low redshifts have higher stellar mass to halo mass ratios than previous expectations and form later than in most theoretical models. Finally, we provide new fitting formulae for star formation histories that are more accurate than the standard declining tau model. Our approach places a wide variety of observations relating to the star formation history of galaxies into a self-consistent framework based on the modern understanding of structure formation in LCDM. Constraints on the stellar mass-halo mass relationship and star formation rates are available for download at http://www.peterbehroozi.com/data.html .Comment: Revised to match ApJ accepted version, with additional corrections to Figs. 18+19 (superseding published version

Systematic review and meta-analysis of reduction in all-cause mortality from walking and cycling and shape of dose response relationship

BACKGROUND AND OBJECTIVE: Walking and cycling have shown beneficial effects on population risk of all-cause mortality (ACM). This paper aims to review the evidence and quantify these effects, adjusted for other physical activity (PA). DATA SOURCES: We conducted a systematic review to identify relevant studies. Searches were conducted in November 2013 using the following health databases of publications: Embase (OvidSP); Medline (OvidSP); Web of Knowledge; CINAHL; SCOPUS; SPORTDiscus. We also searched reference lists of relevant texts and reviews. STUDY ELIGIBILITY CRITERIA AND PARTICIPANTS: Eligible studies were prospective cohort design and reporting walking or cycling exposure and mortality as an outcome. Only cohorts of individuals healthy at baseline were considered eligible. STUDY APPRAISAL AND SYNTHESIS METHODS: Extracted data included study population and location, sample size, population characteristics (age and sex), follow-up in years, walking or cycling exposure, mortality outcome, and adjustment for other co-variables. We used random-effects meta-analyses to investigate the beneficial effects of regular walking and cycling. RESULTS: Walking (18 results from 14 studies) and cycling (8 results from 7 studies) were shown to reduce the risk of all-cause mortality, adjusted for other PA. For a standardised dose of 11.25 MET.hours per week (or 675 MET.minutes per week), the reduction in risk for ACM was 11% (95% CI = 4 to 17%) for walking and 10% (95% CI = 6 to 13%) for cycling. The estimates for walking are based on 280,000 participants and 2.6 million person-years and for cycling they are based on 187,000 individuals and 2.1 million person-years. The shape of the dose-response relationship was modelled through meta-analysis of pooled relative risks within three exposure intervals. The dose-response analysis showed that walking or cycling had the greatest effect on risk for ACM in the first (lowest) exposure interval. CONCLUSIONS AND IMPLICATIONS: The analysis shows that walking and cycling have population-level health benefits even after adjustment for other PA. Public health approaches would have the biggest impact if they are able to increase walking and cycling levels in the groups that have the lowest levels of these activities. REVIEW REGISTRATION: The review protocol was registered with PROSPERO (International database of prospectively registered systematic reviews in health and social care) PROSPERO 2013: CRD42013004266

Worldwide use of the first set of physical activity Country Cards: The Global Observatory for Physical Activity - GoPA!

Background: The work of The Global Observatory for Physical Activity-GoPA! is the first global effort to compile standardized country-level surveillance, policy and research data for physical activity in order to better understand how countries and regions address promoting physical activity. GoPA! developed standardized country-specific physical activity profiles (“Country Cards”) to summarize country-level data through 2013. The aim of this study was to assess use of the Country Cards, identify the factors associated with their use, and develop recommendations for supporting country-level physical activity promotion. Methods: Cross sectional internet-based survey conducted between August–October 2016. Target study participants were national physical activity leaders and advocates in academia, government and practice from the GoPA! countries, and members of the International Society of Physical Activity and Health. A Country Card use composite score was created based on the diversity and frequency of use. Statistical analyses on the associations between the composite score and respondent characteristics, country characteristics, barriers and opinions were conducted (including descriptive analyses and a logistic regression with robust standard errors). Results: One hundred forty three participants from 68 countries completed the survey. Use of the Country Cards was associated with being part of the GoPA! network, knowing about the Country Cards, and on the stage of country capacity for physical activity promotion. Country Card knowledge varied by country income group, region and the country specific context. More diverse and frequent use of the cards (highest tertile of the composite score for use) was associated with: 1. Being a country contact vs general participant (OR 18.32–95% CI 5.63–59.55, p = 0.002), and 2. Collaborating with a government representative working in NCDs on a monthly or more frequent contact vs less frequent contact (OR 3.39–95% CI 1.00–11.54, P < 0.05). Conclusions: For the Country Cards to have a broader impact, GoPA! will need to widen its reach beyond the academic sector. With further refinement of the cards, and training in their implementation, they could be an important tool for advancing country capacity for contextually-relevant strategies, actions and timelines for PA promotion