Exercise, Physical Activity, and Exertion over the Business Cycle

As economic recessions reduce employment and wages, associated shifts in time and income constraints would be expected to also impact individuals’ health behaviors. Prior work has focused exclusively on recreational exercise, which typically represents only about 4% of total daily physical exertion. The general presumption in these studies is that, because exercise improves health, if unemployment increases exercise it must also improve health. Yet a person may be laid off from a physically demanding job, exercise more, and still be less physically active than when employed. Thus the relevant question is whether unemployment leads persons to become more physically active. We study this question with the American Time Use Survey (2003-2010), exploring the impact of the business cycle (and specifically the Great Recession) on individuals’ exercise, other uses of time, and physical activity during the day. We also utilize more precise measures of exercise (and all other physical activities), which reflect information on the duration as well as intensity of each component activity, than has been employed in past studies. Using within-state variation in employment and unemployment, we find that recreational exercise tends to increase as employment decreases. In addition, we also find that individuals substitute into television watching, sleeping, childcare, and housework. However, this increase in exercise as well as other activities does not compensate for the decrease in work-related exertion due to job-loss. Thus total physical exertion, which prior studies have not analyzed, declines. These behavioral effects are strongest among low-educated males, which is validating given that the Great Recession led to some of the largest layoffs within the manufacturing, mining, and construction sectors. Due to the concentration of low-educated workers in boom-and-bust industries, the drop in total physical activity during recessions is especially problematic for vulnerable populations and may play a role in exacerbating the SES-health gradient during recessions. We also find some evidence of intra-household spillover effects, wherein individuals respond to shifts in spousal employment conditional on their own labor supply.

Differential Impact of Recent Medicaid Expansions by Race and Ethnicity

Objective. Between 1989 and 1995, expansions in Medicaid eligibility provided publicly financed health insurance to an additional 7 million poor and near-poor children. It is not known whether these expansions affected children’s insurance coverage, use of health care services, or health status differently, depending on their race/ethnicity. The objective of this study was to examine, by race/ethnicity, the impact of the recent Medicaid expansions on levels of uninsured individuals, health care service utilization, and health status of the targeted groups of children. Methods. Using a stratified set of longitudinal data from the National Health Interview Surveys of 1989 and 1995, we compared changes in measures of health insurance coverage, health services utilization, and health status for poor white, black, and Hispanic 1- to 12-year-old children. To control for underlying trends over time, we subtracted 1989 to 1995 changes in these outcomes among nonpoor children from changes among the poor children for each race/ethnicity group. Measures of coverage included uninsured rates and Medicaid rates. Utilization measures included annual probability of visiting a doctor, annual number of doctor visits, and annual probability of hospitalization. Health status measures included self-reported health status and number of restricted-activity days in the 2 weeks before the interview. Differences in means were analyzed with the use of Student’s t tests accounting for the clustering sample design of the National Health Interview Surveys. Results. Among poor children between 1989 and 1995, uninsured rates declined by 4 percentage points for whites, 11 percentage points for blacks, and 19 percentage points for Hispanics. Medicaid rates for these groups increased by 16 percentage points, 22 percentage points, and 23 percentage points, respectively. With respect to utilization, the annual probability of seeing a physician increased 7 percentage points among poor blacks and Hispanics but only 1 percentage point among poor whites (not significant) for children in good, fair, or poor health. Among those in excellent or very good health, the respective increases were 1 percentage point for poor whites (not significant), 7 percentage points for poor blacks, and 3 percentage points for poor Hispanics (not significant). Significant increases in numbers of doctor visits per year were recorded only for poor Hispanics who were in excellent or very good health, whereas significant decreases in hospitalizations were recorded for Hispanics who were in good fair or poor health. Measures of health status remained unchanged for poor children over time. The recorded decreases in uninsured rates and increases in Medicaid coverage remained robust to adjustments for underlying trends for all 3 race/ethnicity groups. With respect to adjusted measures of utilization and health status, the only significant differences found were among poor blacks who were in good, fair, or poor health and who registered increases in the likelihood of hospitalization and in poor Hispanics who were in excellent or very good health and who registered decreases in the numbers of restricted-activity days. Conclusions. Recent expansions in the Medicaid program from 1989 to 1995 produced greater reductions in uninsured rates among poor minority children than among poor white children. Regardless of race/ethnicity, poor children did not seem to experience significant changes during the period of the expansions in either their level of health service utilization or their health status. Reproduced with permission from Pediatrics, Copyright (c) 2001 by the AAP

Isolating the Effect of Major Depression on Obesity: Role of Selection Bias

There is suggestive evidence that rates of major depression have risen markedly in the U.S. concurrent with the rise in obesity. The economic burden of depression, about $100 billion annually, is under-estimated if depression has a positive causal impact on obesity. If depression plays a causal role in increasing the prevalence of obesity, then policy interventions aimed at promoting mental health may also have the indirect benefits of promoting a healthy bodyweight. However, virtually the entire existing literature on the connection between the two conditions has examined merely whether they are significantly correlated, sometimes holding constant a limited set of demographic factors. This study utilizes multiple large-scale nationally-representative datasets to assess whether, and the extent to which, the positive association reflects a causal link from major depression to higher BMI and obesity. While contemporaneous effects are considered, the study primarily focuses on the effects of past and lifetime depression to bypass reverse causality and further assess the role of non-random selection on unobservable factors. There are expectedly no significant or substantial effects of current depression on BMI or overweight/obesity, given that BMI is a stock measure that changes relatively slowly over time. Results are also not supportive of a causal interpretation among males. However, among females, estimates indicate that past or lifetime diagnosis of major depression raises the probability of being overweight or obese by about seven percentage points. Results also suggest that this effect appears to plausibly operate through shifts in food consumption and physical activity. We estimate that this higher risk of overweight and obesity among females could potentially add about 10$9.7 billion) to the estimated economic burden of depression.

Variation in climate sensitivity and feedback parameters during the historical period

We investigate the climate feedback parameter α (W m−2 K−1) during the historical period (since 1871) in experiments using the HadGEM2 and HadCM3 atmosphere general circulation models (AGCMs) with constant preindustrial atmospheric composition and time-dependent observational sea surface temperature (SST) and sea ice boundary conditions. In both AGCMs, for the historical period as a whole, the effective climate sensitivity is ∼2 K (α≃1.7 W m−2 K−1), and α shows substantial decadal variation caused by the patterns of SST change. Both models agree with the AGCMs of the latest Coupled Model Intercomparison Project in showing a considerably smaller effective climate sensitivity of ∼1.5 K (α = 2.3 ± 0.7 W m−2 K−1), given the time-dependent changes in sea surface conditions observed during 1979–2008, than the corresponding coupled atmosphere-ocean general circulation models (AOGCMs) give under constant quadrupled CO2 concentration. These findings help to relieve the apparent contradiction between the larger values of effective climate sensitivity diagnosed from AOGCMs and the smaller values inferred from historical climate change

Low Concentrations of Silver Nanoparticles in Biosolids Cause Adverse Ecosystem Responses under Realistic Field Scenario

A large fraction of engineered nanomaterials in consumer and commercial products will reach natural ecosystems. To date, research on the biological impacts of environmental nanomaterial exposures has largely focused on high-concentration exposures in mechanistic lab studies with single strains of model organisms. These results are difficult to extrapolate to ecosystems, where exposures will likely be at low-concentrations and which are inhabited by a diversity of organisms. Here we show adverse responses of plants and microorganisms in a replicated long-term terrestrial mesocosm field experiment following a single low dose of silver nanoparticles (0.14 mg Ag kg−1 soil) applied via a likely route of exposure, sewage biosolid application. While total aboveground plant biomass did not differ between treatments receiving biosolids, one plant species, Microstegium vimeneum, had 32 % less biomass in the Slurry+AgNP treatment relative to the Slurry only treatment. Microorganisms were also affected by AgNP treatment, which gave a significantly different community composition of bacteria in the Slurry+AgNPs as opposed to the Slurry treatment one day after addition as analyzed by T-RFLP analysis of 16S-rRNA genes. After eight days, N2O flux was 4.5 fold higher in the Slurry+AgNPs treatment than the Slurry treatment. After fifty days, community composition and N2O flux of the Slurry+AgNPs treatment converged with the Slurry. However, the soil microbial extracellular enzymes leucine amino peptidase and phosphatase had 52 and 27% lower activities, respectively, while microbial biomass was 35% lower than the Slurry. We also show that the magnitude of these responses was in all cases as large as or larger than the positive control, AgNO3, added at 4-fold the Ag concentration of the silver nanoparticles

Engineered Nanoparticles Interact with Nutrients to Intensify Eutrophication in a Wetland Ecosystem Experiment

Despite the rapid rise in diversity and quantities of engineered nanomaterials produced, the impacts of these emerging contaminants on the structure and function of ecosystems have received little attention from ecologists. Moreover, little is known about how manufactured nanomaterials may interact with nutrient pollution in altering ecosystem productivity, despite the recognition that eutrophication is the primary water quality issue in freshwater ecosystems worldwide. In this study, we asked two main questions: (1) To what extent do manufactured nanoparticles affect the biomass and productivity of primary producers in wetland ecosystems? (2) How are these impacts mediated by nutrient pollution? To address these questions, we examined the impacts of a citrate‐coated gold nanoparticle (AuNPs) and of a commercial pesticide containing Cu(OH)2 nanoparticles (CuNPs) on aquatic primary producers under both ambient and enriched nutrient conditions. Wetland mesocosms were exposed repeatedly with low concentrations of nanoparticles and nutrients over the course of a 9‐month experiment in an effort to replicate realistic field exposure scenarios. In the absence of nutrient enrichment, there were no persistent effects of AuNPs or CuNPs on primary producers or ecosystem productivity. However, when combined with nutrient enrichment, both NPs intensified eutrophication. When either of these NPs were added in combination with nutrients, algal blooms persisted for \u3e 50 d longer than in the nutrient‐only treatment. In the AuNP treatment, this shift from clear waters to turbid waters led to large declines in both macrophyte growth and rates of ecosystem gross primary productivity (average reduction of 52% ± 6% and 92% ± 5%, respectively) during the summer. Our results suggest that nutrient status greatly influences the ecosystem‐scale impact of two emerging contaminants and that synthetic chemicals may be playing an under‐appreciated role in the global trends of increasing eutrophication. We provide evidence here that chronic exposure to Au and Cu(OH)2 nanoparticles at low concentrations can intensify eutrophication of wetlands and promote the occurrence of algal blooms

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab

Purpose: We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients. Patients and Methods: TCGA microRNA expression data from tumors resected at first diagnosis of glioblastoma in patients treated with bevacizumab at any time during the course of their disease were randomly separated into training (n=50) and test (n=37) groups for model generation. MicroRNA-seq data for 51 patients whose treatment included bevacizumab in the BELOB trial were used as an independent validation cohort. Results: Using penalized regression we identified 8 microRNAs as potential predictors of overall survival in the training set. We dichotomized the response score based on the most prognostic minimum of a density plot of the response scores (log-rank HR=0.16, p=1.2e-5) and validated the profile in the test cohort (one-sided log-rank HR=0.34, p=0.026). Analysis of the profile using all samples in the TCGA glioblastoma dataset, regardless of treatment received, (n=473) showed that the prediction of patient benefit was not significant (HR=0.84, p=0.083) suggesting the profile is specific to bevacizumab. Further independent validation of our microRNA profile in RNA-seq data from patients treated with bevacizumab (alone or in combination with CCNU) at glioblastoma recurrence in the BELOB trial confirmed that our microRNA profile predicted patient benefit from bevacizumab (HR=0.59, p=0.043). Conclusion: We have identified and validated an 8-microRNA profile that predicts overall survival in patients with glioblastoma treated with bevacizumab. This may be useful for identifying patients who are likely to benefit from this agent