Examining Changes in Food Security, Perceived Stress, and Dietary Intake in a Cohort of Low-Wage Workers Experiencing an Increase in Hourly Wage

OBJECTIVE

To determine whether an increase in hourly wages was associated with changes in food security and perceived stress among low-wage workers. We also determined whether changes in food security and stress were associated with changes in diet.

SETTING

Wages is a prospective cohort study following 974 low-wage workers in Minneapolis, MN, where an ordinance is incrementally increasing minimum wage to US$15/hr from 2018 to 2022, and a comparison community with no minimum wage ordinance (Raleigh, NC). Interaction models were estimated using generalized estimating equations.

PARTICIPANTS

Analyses used two waves of data (2018 [baseline], 2019) and included 219 and 321 low-wage workers in Minneapolis and Raleigh (respectively).

RESULTS

Average hourly wages increased from US$9.77 (SD US$1.69) to US$11.67 (SD US$4.02). Changes in wages were not associated with changes in food security (odds ratio = 1.05, 95% confidence interval [CI] [0.89, 1.23], p = .57) or stress (β = -0.01, 95% CI [-0.04, 0.03], p = .70) after 1 year of policy implementation. Changes in food security were not associated with changes in diet. However, we found significant changes in the frequency of fruit and vegetable intake across time by levels of stress, with decreased intake from Wave 1 to 2 at low levels of stress, and increased intake at high levels of stress (incidence rate ratio = 1.17, 95% CI [1.05, 1.31], p = .01).

CONCLUSIONS

Changes in wages were not associated with changes in food security or stress in a sample of low-wage workers. Future research should examine whether full implementation of a minimum wage increase is associated with changes in these outcomes.

Maximally localized Wannier functions, interaction models, and fractional quantum anomalous Hall effect in twisted bilayer MoTe2

We investigate the moiré band structures and the strong correlation effects in twisted bilayer MoTe[Formula: see text] for a wide range of twist angles, employing a combination of various techniques. Using large-scale first-principles calculations, we pinpoint realistic continuum modeling parameters, subsequently deriving the maximally localized Wannier functions for the top three moiré bands. Simplifying our model with reasonable assumptions, we obtain a minimal two-band model, encompassing Coulomb repulsion, correlated hopping, and spin exchange. Our minimal interaction models pave the way for further exploration of the rich many-body physics in twisted MoTe[Formula: see text]. Furthermore, we explore the phase diagrams of the system through Hartree-Fock approximation and exact diagonalization (ED). Our two-band ED analysis underscores significant band-mixing effects in this system, which enlarge the optimal twist angle for fractional quantum anomalous Hall states.

The Scaling and Modeling of Pay and the Robustness of the Effect of Core Self Evaluations on Career Success

A number of recent studies used nominal pay in estimating the effects of individual differences, particularly core-self-evaluation, on career success. We show that this practice may lead to results that are substantively different from the results when the logarithm of pay is used. We conduct three constructive replications of previous studies, and argue that substantive conclusion based on the results of nominal pay are misleading.

Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples

The aim of this study was to obtain the growth parameters of specific spoilage micro-organisms previously isolated in minced pork (MP) samples and to develop a three-spoilage species interaction model under different storage conditions. Naturally contaminated samples were used to validate this approach by considering the effect of the food microbiota. Three groups of bacteria were inoculated on irradiated samples, in mono- and in co-culture experiments (n = 1152): Brochothrix thermosphacta, Leuconostoc gelidum, and Pseudomonas spp. (Pseudomonas fluorescens and Pseudomonas fragi). Samples were stored in two food packaging [food wrap and modified atmosphere packaging (CO2 30%/O2 70%)] at three isothermal conditions (4, 8, and 12°C). Analysis was carried out by using both 16S rRNA gene amplicon sequencing and classical microbiology in order to estimate bacterial counts during the storage period. Growth parameters were obtained by fitting primary (Baranyi) and secondary (square root) models. The food packaging shows the highest impact on bacterial growth rates, which in turn have the strongest influence on the shelf life of food products. Based on these results, a three-spoilage species interaction model was developed by using the modified Jameson-effect model and the Lotka Volterra (prey-predator) model. The modified Jameson-effect model showed slightly better performances, with 40-86% out of the observed counts falling into the Acceptable Simulation Zone (ASZ). It only concerns 14-48% for the prey-predator approach. These results can be explained by the fact that the dynamics of experimental and validation datasets seems to follow a Jameson behavior. On the other hand, the Lotka Volterra model is based on complex interaction factors, which are included in highly variable intervals. More datasets are probably needed to obtained reliable factors, and so better model fittings, especially for three- or more-spoilage species interaction models. Further studies are also needed to better understand the interaction of spoilage bacteria between them and in the presence of natural microbiota.

Age-space-time CAR models in Bayesian disease mapping

Mortality counts are usually aggregated over age groups assuming similar effects of both time and region, yet the spatio-temporal evolution of cancer mortality rates may depend on changing age structures. In this paper, mortality rates are analyzed by region, time period and age group, and models including space-time, space-age, and age-time interactions are considered. The integrated nested Laplace approximation method, known as INLA, is adopted for model fitting and inference in order to reduce computing time in comparison with Markov chain Monte Carlo (McMC) methods. The methodology provides full posterior distributions of the quantities of interest while avoiding complex simulation techniques. The proposed models are used to analyze prostate cancer mortality data in 50 Spanish provinces over the period 1986-2010. The results reveal a decline in mortality since the late 1990s, particularly in the age group [65,70), probably because of the inclusion of the PSA (prostate-specific antigen) test and better treatment of early-stage disease. The decline is not clearly observed in the oldest age groups. Copyright © 2016 John Wiley & Sons, Ltd.