The development and application of a sustainable diets framework for policy analysis: A case study of Nepal

The objectives of this study were to 1) develop a policy analysis framework for examining the components of a sustainable diet and 2) to apply its use to three relevant national polices in Nepal. We developed a policy analysis framework using existing literature and applied the framework to three Nepalese policies: Nepal’s Multisectoral Nutrition Plan (MSNP) 2013–2017, Agricultural Development Strategy (ADS) 2015–2035 and National Biodiversity Strategy and Action Plan (NBSAP) 2014–2020. Each policy was coded independently by two researchers to examine whether the different components of the sustainable diets framework were mentioned and if they had associated policy actions. We then used a health policy analysis tool to examine the overall quality of each policy. The ADS mentioned the most (89%) components of the sustainable diets framework as compared to the NBSAP (58%) and the MSNP (70%). If all three policies were fully implemented they would address all but one of the components of a sustainable diet, with the potential to deliver for health and the environment. However, there was a lack of clarity regarding how the resources to accomplish the policy objectives would be obtained as well as insufficient detail regarding the policies’ monitoring and evaluation frameworks. The sustainable diets framework developed in this study enables the identification of gaps where policies need to broaden their focus in order to incorporate a more holistic view of the food system. This will become increasingly important as climate change continues to persist and the need for more resilient food systems becomes more recognized

Incorporating Alternative Polygenic Risk Scores into the BOADICEA Breast Cancer Risk Prediction Model

Background: The multifactorial risk prediction model BOADI-CEA enables identification of women at higher or lower risk of developing breast cancer. BOADICEA models genetic susceptibility in terms of the effects of rare variants in breast cancer susceptibility genes and a polygenic component, decomposed into an unmeasured and a measured component -the polygenic risk score (PRS). The current version was developed using a 313 SNP PRS. Here, we evaluated approaches to incorporating this PRS and alternative PRS in BOADICEA.Methods: The mean, SD, and proportion of the overall polygenic component explained by the PRS (a2) need to be estimated. a was estimated using logistic regression, where the age-specific log-OR is constrained to be a function of the age-dependent polygenic relative risk in BOADICEA; and using a retrospective likelihood (RL) approach that models, in addition, the unmeasured polygenic component.Results: Parameters were computed for 11 PRS, including 6 variations of the 313 SNP PRS used in clinical trials and imple-mentation studies. The logistic regression approach underestimates a, as compared with the RL estimates. The RL a estimates were very close to those obtained by assuming proportionality to the OR per 1 SD, with the constant of proportionality estimated using the 313 SNP PRS. Small variations in the SNPs included in the PRS can lead to large differences in the mean.Conclusions: BOADICEA can be readily adapted to different PRS in a manner that maintains consistency of the model.Impact : The methods described facilitate comprehensive breast cancer risk assessment

Smc5/6 coordinates formation and resolution of joint molecules with chromosome morphology to ensure meiotic divisions

During meiosis, Structural Maintenance of Chromosome (SMC) complexes underpin two fundamental features of meiosis: homologous recombination and chromosome segregation. While meiotic functions of the cohesin and condensin complexes have been delineated, the role of the third SMC complex, Smc5/6, remains enigmatic. Here we identify specific, essential meiotic functions for the Smc5/6 complex in homologous recombination and the regulation of cohesin. We show that Smc5/6 is enriched at centromeres and cohesin-association sites where it regulates sister-chromatid cohesion and the timely removal of cohesin from chromosomal arms, respectively. Smc5/6 also localizes to recombination hotspots, where it promotes normal formation and resolution of a subset of joint-molecule intermediates. In this regard, Smc5/6 functions independently of the major crossover pathway defined by the MutLγ complex. Furthermore, we show that Smc5/6 is required for stable chromosomal localization of the XPF-family endonuclease, Mus81-Mms4Eme1. Our data suggest that the Smc5/6 complex is required for specific recombination and chromosomal processes throughout meiosis and that in its absence, attempts at cell division with unresolved joint molecules and residual cohesin lead to severe recombination-induced meiotic catastroph

The Impact of Advocacy Organizations on Low-Income Housing Policy in U.S. Cities

Financial support for affordable housing competes with many other municipal priorities. This work seeks to explain the variation in support for affordable housing among U.S. cities with populations of 100,000 or more. Using multivariate statistical analysis, this research investigates political explanations for the level of city expenditures on housing and community with a particular interest in the influence of housing advocacy organizations (AOs). Data for the model were gathered from secondary sources, including the U.S. Census and the National Center for Charitable Statistics. Among other results, the analysis indicates that, on average, the political maturity of AOs has a statistically significant, positive effect on local housing and community development expenditures

Moving forward with backwards compatibility: Translating wrist accelerometer data

Purpose: To provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children’s moderate-to-vigorous physical activity (MVPA) from a range of cut-points applied to hip-worn ActiGraph data. Methods: This is a secondary analysis of three studies with concurrent 7-day accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children aged 9-12 years. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350 and 400 mg from wrist acceleration data (<5 s epoch) was calculated for comparison to MVPA estimated from widely used children’s hip-worn ActiGraph MVPA cut-points (Freedson/Trost 1100 counts per minute (cpm); Pate 1680 cpm; Evenson 2296 cpm; Puyau 3200 cpm) with epochs of <5, 15 and 60 s. Results: The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut-points determined from 70% of the sample and cross-validated with the remaining 30% were: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (ICC>0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC>0.67); Evenson = ENMO 250+ mg for 0.69) and ENMO 300+ mg for 60 s epochs (ICC=0.73); Puyau = ENMO 300+ mg for <5 s epochs (ICC=0.73), ENMO 350+ mg for 15 s epochs (ICC=0.73), ENMO 400+ mg for 60 s epochs (ICC=0.65). Agreement was robust with cross-validation ICCs=0.62-0.71 and means within ?7.8?±4.9% of MVPA estimates from ActiGraph cut-points, except Puyau 60 s epochs (ICC=0.42). Conclusion: Incremental ENMO thresholds enable children’s acceleration data measured at the wrist to be simply and directly compared, at a group level, to past estimates of MVPA from hip-worn ActiGraphs across a range of cut-points

HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials.

BACKGROUND: Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target. METHODS: We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis. FINDINGS: Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05-0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18-0·43), waist circumference (0·32 cm, 0·16-0·47), plasma insulin concentration (1·62%, 0·53-2·72), and plasma glucose concentration (0·23%, 0·02-0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00-1·05); the rs12916-T allele association was consistent (1·06, 1·03-1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18-1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10-0·38 in all trials; 0·33 kg, 95% CI 0·24-0·42 in placebo or standard care controlled trials and -0·15 kg, 95% CI -0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9-6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06-1·18 in all trials; 1·11, 95% CI 1·03-1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04-1·22 in intensive-dose vs moderate dose trials). INTERPRETATION: The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition. FUNDING: The funding sources are cited at the end of the paper

Meaning and Function in the Theory of Consumer Choice: Dual Selves in Evolving Networks

Building on the philosophy of Charles Sanders Peirce, recent advances in biosemiotics have resulted into a concise framework for the analysis of signs in living systems. This paper explores the potential for economics and shows how biosemiotics can integrate two different research agendas, each of which are also connected with biological theories, namely neuroeconomics and the theory of networks. I introduce the triadic conceptual framework established by Peirce which distinguishes between object, sign and interpretant and the corresponding causal forces in evolving hierarchical systems. This framework is used to systematize recent results of neuroeconomics in the form of the dual selves approach, following early contributions of James Coleman, partitioning the individual into the acting self and the object self. This distinction implies that there is a fundamental information asymmetry between the two selves. Against this background, the semeiotic process is an information generating and processing dynamics, which is driven by the internal selection of classificatory schemes of actions chosen and the population level dynamics of sign selection, with mimetic behavior as a driver. This can be further analyzed by means of the theory of signal selection. A central insight is that the internal information gap between acting self and object self implies a systematic role of sign processing in social networks for any kind of consumer choice. I exemplify my approach with empirical references to food consumption as a most universal and simple form of consumer choice