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Cropper discusses a recent working paper that assesses the full benefits and costs of the groundbreaking law’s many programs to protect the environment.

Scientific evidence regarding sexual minority populations has generally come from studies based on two types of samples: community-derived samples and probability samples. Probability samples are lauded as the gold standard of population research for their ability to represent the population of interest. However, while studies using community samples lack generalizability, they are often better able to assess population-specific concerns (e.g., minority stress) and are collected more rapidly, allowing them to be more responsive to changing population dynamics. Given these advantages, many sexual minority population studies rely on community samples. To identify how probability and community samples of sexual minorities are similar and different, we compared participant characteristics from two companion samples from the  Generations Study , each designed with the same demographic profile of U.S. sexual minority adults in mind. The first sample was recruited for a national probability survey, whereas the second was recruited for a multicommunity sample from four U.S. cities. We examined sociodemographic differences between the samples. Although there were several statistical differences between samples, the effect sizes were small for sociodemographic characteristics that defined the sample inclusion criteria: sex assigned at birth, race/ethnicity, and age cohort. The samples differed across other characteristics: bisexual respondents, respondents with less education, and those living in non-urban areas were underrepresented in the community sample. Our findings offer insights for recruiting community samples of sexual minority populations and for measuring sexual identity on probability surveys. They also bolster confidence in well-designed community samples as sources for data on sexual minority populations.

Background Atmospheric particulate matter (PM) has been associated with endothelial dysfunction, an early marker of cardiovascular risk. Our aim was to extend this research to a genetically homogenous, geographically stable rural population using location-specific moving-average air pollution exposure estimates indexed to the date of endothelial function measurement. Methods We measured endothelial function using brachial artery flow-mediated dilation (FMD) in 615 community-dwelling healthy Amish participants. Exposures to PM < 2.5 μm (PM 2.5 ) and PM < 10 μm (PM 10 ) were estimated at participants’ residential addresses using previously developed geographic information system-based spatio-temporal models and normalized. Associations between PM exposures and FMD were evaluated using linear mixed-effects regression models, and polynomial distributed lag (PDL) models followed by Bayesian model averaging (BMA) were used to assess response to delayed effects occurring across multiple months. Results Exposure to PM 10  was consistently inversely associated with FMD, with the strongest (most negative) association for a 12-month moving average (− 0.09; 95% CI: − 0.15, − 0.03). Associations with PM 2.5  were also strongest for a 12-month moving average but were weaker than for PM 10  (− 0.07; 95% CI: − 0.13, − 0.09). Associations of PM 2.5  and PM 10  with FMD were somewhat stronger in men than in women, particularly for PM 10 . Conclusions Using location-specific moving-average air pollution exposure estimates, we have shown that 12-month moving-average estimates of PM 2.5  and PM 10  exposure are associated with impaired endothelial function in a rural population.

As a strategy for combating physical inactivity, obesity, and other health conditions, the apperception of greenspace and importance of human-nature relationships have increased in recent decades. With this raised awareness in greenspace, the development of park auditing tools has been positioned primarily in the material conditions (e.g., physical environmental conditions) of parks. An examination of existing park auditing tools has shown that by focusing on particular material conditions, built environment and active living scholars have set aside other characteristics, namely, those that consider the user (e.g., the active human), as a separate concern from the focus of these tools. We have sought to engage with these tools to examine how they can be more effective in analyzing both the physical and human elements of parks and other natural environments.

Having first reached epidemic proportions in coastal metropolitan areas, COVID-19 has spread 4 around the country. Reported case rates vary across counties from zero to 125 per thousand 5 population (around a state prison in the rural county of Trousdale, Tennessee). Overall, rural 6 counties are underrepresented relative to their share of the population, but a growing proportion 7 of all daily cases and deaths have been reported in rural counties. This analysis uses daily 8 reports for all counties to present the trends and distribution of COVID-19 cases and deaths in 9 rural counties, from late March to May 16, 2020. I describe the relationship between population 10 density and case rates in rural and non-rural counties. Then I focus on noteworthy outbreaks 11 linked to prisons, meat and poultry plants, and nursing homes, many of which are linked to 12 high concentrations of Hispanic, American Indian, and Black populations. The growing 13 epidemic in rural counties is apparently driven by outbreaks concentrated in these institutional 14 settings, which are conducive to transmission. The impact of the epidemic in rural areas may 15 be heightened due to their weaker health infrastructure and more vulnerable populations, 16 especially due to age, socioeconomic status, and health conditions. As a result, the epidemic 17 may contribute to the ongoing decline of health, economic, and social conditions in rural areas.

We study how consumers make brand choices when they have limited information. In a market of experience goods with frequent product entry and exit, consumers face two types of information problems: first, they have limited information about a product’s existence; second, even if they know a product exists, they do not have full information about its quality until they purchase and consume it. In this chapter, we incorporate purchase experience and brand advertising as two sources of information and examine how consumers use them in a dynamic process. The model is estimated using the Nielsen Homescan data in Los Angeles, which consist of grocery shopping history for 1,402 households over 6 years. Taking ready-to-eat cereal as an example, we find that consumers learn about new products quickly and form strong habits. More specifically, advertising has a significant effect in informing consumers of a product’s existence and signaling product quality. However, advertising’s prestige effect is not significant. We also find that incorporating limited information about a product’s existence leads to larger estimates of the price elasticity. Based on the structural estimates, we simulate consumer choices under three counterfactual experiments to evaluate brand marketing strategies and a policy on banning children-oriented cereal advertising. Simulation suggests that the advertising ban encourages consumers to consume less sugar and more fiber, but their expenditures are also higher because they switch to family and adult brands, which are more expensive.

Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average.

BACKGROUND: Past research shows that among individuals with substance use disorders, the presence of a co-occurring mental illness can influence the initiation, course, and success of behavioral health treatment, but little research has examined people with opioid use disorder (OUD) specifically. METHODS: Using the 2008-2014 National Survey on Drug Use and Health, this study examines the utilization of substance use disorder and mental health treatment among individuals with OUD and different degrees of mental illness severity. The study also examined types of treatment, perceived unmet need for treatment, and barriers to care. RESULTS: 47% of individuals with OUD and co-occurring mild/moderate mental illness did not receive any behavioral health treatment, and 21% of those with co-occurring serious mental illnesses did not receive any behavioral health treatment. Among those with OUD and co-occurring mild/moderate mental illness, 16% reported receiving both substance use disorder and mental health treatment; among those with co-occurring serious mental illness the rate was 32%. The most common form of treatment was prescription medication for mental health, and this was true regardless of whether or not the individual had any mental illness. More than 50% of the study population reported financial difficulties as a barrier to treatment. CONCLUSION: A high proportion of individuals with OUD and co-occurring mental illness are not receiving needed care. However, nearly one in five of those with OUD but no diagnosed mental illness is receiving prescription medication for mental illness. These findings suggest that there is a need to better facilitate access to and coordinate behavioral health care across settings for individuals with OUD. Published by Elsevier Inc.

PURPOSE: We aimed to estimate latent classes of concurrent polysubstance use and test for sexual orientation differences in latent class memberships with representative data from adolescents living in 19 U.S. states. We also tested whether sex, race/ethnicity, and age moderated the sexual identity differences in polysubstance use class memberships. METHODS: We analyzed data from 119,437 adolescents from 19 states who participated in the 2015 Youth Risk Behavior Survey. Latent class analysis characterized polysubstance use patterns based on self-reported frequency of lifetime and past-month use of alcohol (including heavy episodic drinking), tobacco (cigarettes, cigars, and smokeless tobacco), and marijuana. Multinomial logistic regression models tested differences in latent class memberships by sexual identity. Interaction terms tested whether sex, race/ethnicity, and age moderated the sexual identity differences in polysubstance use class memberships. RESULTS: A six-class model of polysubstance use fit the data best and included nonusers (61.5%), experimental users (12.2%), marijuana-alcohol users (14.8%), tobacco-alcohol users (3.8%), medium-frequency three-substance users (3.6%), and high-frequency three-substance users (4.1%). Gay/lesbian- and bisexual-identified adolescents had significantly higher odds than heterosexual-identified adolescents of being in all of the user classes compared with the nonuser class. These sexual identity differences in latent polysubstance use class memberships were generally larger for females than for males, varied occasionally by race/ethnicity, and were sometimes larger for younger ages. CONCLUSION: Compared with their heterosexual peers, gay/lesbian and bisexual adolescents-especially females-are at heightened risk of engaging in multiple types of polysubstance use. Designing, implementing, and evaluating interventions will likely reduce these sexual orientation disparities.

Air pollution is a persistent and well-established public health problem in India: emissions from coal-fired power plants have been associated with over 80,000 premature deaths in 2015. Premature deaths could rise by four to five times this number by 2050 without additional pollution controls. We site a model 500 MW coal-fired electricity generating unit at eight locations in India and examine the benefits and costs of retrofitting the plant with a flue-gas desulfurization unit to reduce sulfur dioxide emissions. We quantify the mortality benefits associated with the reduction in sulfates (fine particles) and value these benefits using estimates of the value per statistical life transferred to India from high income countries. The net benefits of scrubbing vary widely by location, reflecting differences in the size of the exposed population. They are highest at locations in the densely populated north of India, which are also among the poorest states in the country.