The Obamacare Opportunity: Implementing the Affordable Care Act to Improve Health, Reduce Hardship, and Grow the Economy for All Californians

This report describes how California can take advantage of ACA implementation to increase access both to health coverage and to vital safety net and work support programs.In Section I, we describe California's public benefit take up problem. We identify the take up rates of the key safety net and work support programs, barriers to greater participation, and the benefits of increasing participation in such programs.In Section II, we describe how ACA implementation can increase take up rates for health insurance and public benefit programs. States can expand integration infrastructure and operations across a broad range of programs and the federal government will pay most of the costs.In Section III, we set forth various policy options for integrating California's Marketplace with public benefit programs. We describe California's existing integration efforts and present ACA and non-ACA best practices from other states regarding take up strategies.In Section IV, we make recommendations focused on a single goal -- increasing the take up rate of safety net and work support programs to improve health, reduce hardship, and grow the economy for all Californians

County-Specific Net Migration by Five-Year Age Groups, Hispanic Origin, Race and Sex 2000-2010

This report documents the methodology used to prepare county-level, net migration estimates by five-year age cohorts and sex, and by race and Hispanic origin, for the intercensal period from 2000 to 2010. The estimates were prepared using a vital statistics version of the forward cohort residual method (Siegel and Hamilton 1952) following the techniques used to prepare the 1990 to 2000 net migration estimates (Voss, McNiven, Johnson, Hammer, and Fuguitt 2004) as described in detail below. These numbers (and the net migration rates derivable from them) extend the set of decennial estimates of net migration that have been produced following each decennial census beginning with 1960 (net migration for the 1950s: Bowles and Tarver, 1965; 1960s: Bowles, Beale and Lee, 1975; 1970s: White, Mueser and Tierney, 1987; 1980s: Fuguitt, Beale, and Voss 2010; and 1990s: Voss, McNiven, Hammer, Johnson and Fuguitt, 2004)

Transversals via regularity

Given graphs $G_1,\ldots,G_s$ all on the same vertex set and a graph $H$ with $e(H) \leq s$, a copy of $H$ is transversal or rainbow if it contains at most one edge from each $G_c$. When $s=e(H)$, such a copy contains exactly one edge from each $G_i$. We study the case when $H$ is spanning and explore how the regularity blow-up method, that has been so successful in the uncoloured setting, can be used to find transversals. We provide the analogues of the tools required to apply this method in the transversal setting. Our main result is a blow-up lemma for transversals that applies to separable bounded degree graphs $H$. Our proofs use weak regularity in the $3$-uniform hypergraph whose edges are those $xyc$ where $xy$ is an edge in the graph $G_c$. We apply our lemma to give a large class of spanning $3$-uniform linear hypergraphs $H$ such that any sufficiently large uniformly dense $n$-vertex $3$-uniform hypergraph with minimum vertex degree $\Omega(n^2)$ contains $H$ as a subhypergraph. This extends work of Lenz, Mubayi and Mycroft

Statin usage, vascular diagnosis and vascular risk factors in Parkinson's disease

Background and aims: Vascular disease is a common comorbidity in Parkinson’s disease patients. Statins are potentially neuroprotective for Parkinson’s disease through non-vascular mechanisms. We investigated prevailing statin use in a Parkinson’s disease cohort. Methods and results: Data on diagnostic indication for statins, anti-Parkinson therapy, vascular risk factors, and statin prescription, were obtained from electronic medical record review for consecutive Parkinson’s disease patients. The ASsessing cardiac risk using Scottish Intercollegiate Guidelines Network system was used to calculate future cardiovascular risk and identify those warranting statin use. Of 441 patients included, 59.9% were male, with a mean age of 68.9 years (standard deviation 10.3). One hundred and seventy-four (39.5%) patients had at least one diagnostic indication for statin use, of whom 136 (78.2%) were prescribed a statin. In the 267 (60.5%) cases without a diagnostic indication, 54 (20.2%) were excluded owing to age limitations defined in ASsessing cardiac risk using Scottish Intercollegiate Guidelines Network. Of the remaining 213, 62 (29.1%) had an ASsessing cardiac risk using Scottish Intercollegiate Guidelines Network score in the recommended range for statin therapy, of whom 15 (24.1%) were prescribed statins. Conclusion: There is suboptimal implementation of statin therapy in Parkinson’s disease patients. Given the possible neuroprotective effects of statins in Parkinson’s disease in addition to reducing cardiovascular risk, reasons for suboptimal implementation warrant further investigation

Can Parents’ Growth Mindset and Role Modelling Address STEM Gender Gaps?

Despite widespread interest and value in introducing and better-preparing students to enter the science, technology, engineering, and mathematics (STEM) fields, a gender gap persists as women are underrepresented among STEM jobs and degree completion. Although some work has evaluated whether interventions and certain pedagogical practices improve growth mindset, little is known about the mediating role of parents and whether those effects are more pronounced for females. In this study, we explore the extent to which the mindsets of a student’s parents regarding math ability influence the student’s mindset in math ability and longer-term STEM-related outcomes. We pay particular attention to differences between male and female students. We also explore if student outcomes can be attributable to a role modeling effect through parental occupation type (i.e., whether the parent has a job in the STEM field or not) or if there is a remaining direct inheritance from parent growth mindset after controlling for parental occupation. We test these hypotheses in the Education Longitudinal Study of 2002 (ELS), a nationally-representative data set where data for high school students are linked to data from their parents and followed throughout secondary and postsecondary school. Estimating regression models while controlling for a rich set of covariates, we first show that students who exhibit greater levels of growth mindset, self-efficacy, and effort, particularly when it comes to their math coursework, demonstrate higher math achievement, complete more advanced math courses, are more likely to earn a college degree in a STEM field, and are more interested in and likely to actually enter the STEM fields. We then show that parent growth mindset is positively associated with these student non-cognitive skills and outcomes, though the effect seems to fade away over time. On the other hand, although parental occupation type does not consistently explain short- and medium-term STEM outcomes, it does explain longer-term outcomes in early adulthood like graduating with a STEM degree and working in the STEM field. Thus, parent growth mindset and any role modelling effect channeled through parental occupation appear to independently influence student outcomes

Parental Occupational Choice and Children\u27s Entry into a Stem Field

We explore the intergenerational occupational transmission between parents and their children as it pertains to entry into the STEM field. Using the Education Longitudinal Study of 2002, we study student’s aspirations to work in a STEM field and eventual STEM education and employment. We show how these patterns change depending on whether the student’s parents work in a STEM field. We find strong effects of parental occupation type on student’s STEM outcomes that are heterogeneous by student gender. High school boys are more likely to aspire to work in STEM if one of their parents do so. By adulthood, both boys and girls have a higher probability of majoring and working in a STEM field if their parents also do, and in this case, estimated effects are stronger for girls despite a lack of effects on high school girls’ aspirations. For girls but not for boys, having a parent working in STEM increases the probability of entering the STEM field in adulthood above and beyond aspirations to enter the STEM field during adolescence

Bayesian Analysis of Multivariate Matched Proportions with Sparse Response

Multivariate matched proportions (MMP) data appears in a variety of contexts including post-market surveillance of adverse events in pharmaceuticals, disease classification, and agreement between care providers. It consists of multiple sets of paired binary measurements taken on the same subject. While recent work proposes non-Bayesian methods to address the complexities of MMP data, the issue of sparse response, where no or very few "yes" responses are recorded for one or more sets, is unaddressed. The presence of sparse response sets results in underestimates of variance, loss of coverage, and lowered power in existing methods. Bayesian methods have not previously been considered for MMP data but provide a useful framework when sparse responses are present. In particular, the Bayesian probit model provides an elegant solution to the problem of variance underestimation. We examine three approaches built on that model: a naive analysis with flat priors, a penalized analysis using half-Cauchy priors on the mean model variances, and a multivariate analysis with a Bayesian functional principal component analysis (FPCA) to model the latent covariance. We show that the multivariate analysis performs well on MMP data with sparse responses and outperforms existing non-Bayesian methods. In a re-analysis of data from a study of the system of care (SOC) framework for children with mental and behavioral disorders, we are able to provide a more complete picture of the relationships in the data. Our analysis provides additional insights into the functioning on the SOC that a previous univariate analysis missed

Metabolomic Profiling to Identify Predictors of Response to Vitamin E for Non-Alcoholic Steatohepatitis (NASH)

Vitamin E was recently shown to improve hepatic histology in a randomized controlled trial of pioglitazone or vitamin E for nonalcoholic steatohepatitis (PIVENS). The current study utilized samples collected in the PIVENS trial to identify: (1) baseline metabolomic profiles that could identify who would respond to vitamin E treatment and (2) end of treatment metabolomic profiles reflective of histologic improvement. A comprehensive analysis of metabolomics profiles (n = 547) quantified by mass spectrometry was performed in vitamin E responders (n = 16), vitamin E non-responders (n = 15), and placebo responders (n = 15). At baseline, phenyl-propionic acid (Odds ratio: 29.4, p\u3c0.01), indole-propionic acid levels (Odds ratio: 16.2, p\u3c0.01) were directly associated with a subsequent histologic response to vitamin E treatment whereas γ-carboxyethylhydroxychroman (CEHC) levels were inversely related to histologic response. Adjusting for baseline values by analysis of covariance, the end of treatment levels of gamma-glutamyl leucine (Fold change: 0.82, p\u3c0.02) and gamma-glutamyl valine (Fold change: 0.8, p\u3c0.03) were significantly lower in vitamin E responders compared to non-responders. The levels of gamma-glutamyl transpeptidase were not significantly different across the two groups. Subjects receiving placebo who demonstrated a histologic improvement also demonstrated lower levels of gamma-glutamylated amino acids (leucine, valine and isoleucine) compared to vitamin E non-responders. These data provide exploratory proof that there are measurable differences in the metabolic profile of subjects who are likely (vs unlikely) to respond to vitamin E treatment for NASH and in those experiencing histologic improvement (vs no improvement) on treatment and support further studies to validate these biomarkers

Near-Unity Unselective Absorption in Sparse InP Nanowire Arrays

We experimentally demonstrate near-unity, unselective absorption, broadband, angle-insensitive, and polarization-independent absorption, in sparse InP nanowire arrays, embedded in flexible polymer sheets via geometric control of waveguide modes in two wire motifs: (i) arrays of tapered wires and (ii) arrays of nanowires with varying radii. Sparse arrays of these structures exhibit enhanced absorption due to strong coupling into the first order azimuthal waveguide modes of individual nanowires; wire radius thus controls the spectral region of the absorption enhancement. Whereas arrays of cylindrical wires with uniform radius exhibit narrowband absorption, arrays of tapered wires and arrays with multiple wire radii expand this spectral region and achieve broadband absorption enhancement. Herein, we present an economic, top-down lithographic/etch fabrication method that enables fabrication of multiple InP nanowire arrays from a single InP wafer with deliberate control of nanowire radius and taper. Using this method, we create sparse tapered and multiradii InP nanowire arrays and demonstrate optical absorption that is broadband (450–900 nm), angle-insensitive, and near-unity (>90%) in roughly 100 nm planar equivalence of InP. These highly absorbing sparse nanowire arrays represent a promising approach to flexible, high efficiency optoelectronic devices, such as photodetectors, solar cells, and photoelectrochemical devices