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Migrant domestic workers provide essential services to the families they live with, but they are not considered a part of the family. As a group, they are not well-integrated into the society and often suffer from social isolation. In this article, we explore the potential health buffering effects of their personal network, in terms of family and friendship ties in both the local community and their home country. Existing literature provides inconsistent evidence on who and what matters more, with regard to the nature, strength, and geographic locations of individual personal networks. Using data from the Survey of Migrant domestic Workers in Hong Kong (2017), we find that family ties are extremely important. The presence of family members in Hong Kong as well as daily contact with family, regardless of location, are associated with better self-reported health. Only daily contact with friends in Hong Kong, not with friends in other countries, promotes better health. We also find evidence that the protective effects of family and friends networks depend on each other. Those foreign domestic workers with families in Hong Kong but also maintain daily contact with friends have the best self-reported health among all.

Students with chronic health conditions miss more school days than their peers and are at increased risk for performing worse on standardized tests and not completing a high school degree. University-based researchers, state government leaders, and a local county school system collaborated to use existing health and academic data to (1) evaluate the strength of the relationship between health status and school performance (absenteeism, grades) and (2) describe the health status of students who are chronically absent. Analyses included descriptive statistics, chi-square tests, negative binomial regression models, and estimated marginal means. The most common health conditions among the 3,663 kindergarten through Grade 12 students were ADD (attention deficit disorder)/ADHD (attention deficit hyperactivity disorder), asthma, migraine headaches, mental health conditions, and eczema/psoriasis/skin disorders. After controlling for covariates, having asthma or a mental health diagnosis was positively associated with absences; and having an ADD/ADHD or mental health diagnosis was negatively associated with GPA (grade point average). Chronically absent students had significantly lower GPAs, and a higher number of health conditions than other students. The success of this demonstration project encourages strengthening existing collaborations and establishing new multidisciplinary partnerships to analyze existing data sources to learn more about the relationship between student health and academic achievement. Moreover, connecting health status to academic achievement might be a chief tactic for advocating for additional resources to improve the care and management of chronic disease conditions among students.

  BACKGROUND: Stroke is a leading cause of morbidity and mortality in the United States. Associations between short-term exposures to particulate matter (PM) air pollution and stroke are inconsistent. Many prior studies have used administrative and hospitalization databases where misclassification of the type and timing of the stroke event may be problematic. METHODS: In this case-crossover study, we used a nationwide kriging model to examine short-term ambient exposure to PM10 and PM2.5 and risk of ischemic and hemorrhagic stroke among men enrolled in the Health Professionals Follow-up Study. Conditional logistic regression models were used to obtain estimates of odds ratios (OR) and 95% confidence intervals (CI) associated with an interquartile range (IQR) increase in PM2.5 or PM10. Lag periods up to 3 days prior to the stroke event were considered in addition to a 4-day average. Stratified models were used to examine effect modification by patient characteristics. RESULTS: Of the 727 strokes that occurred between 1999 and 2010, 539 were ischemic and 122 were hemorrhagic. We observed positive statistically significant associations between PM10 and ischemic stroke (ORlag0-3 = 1.26; 95% CI: 1.03-1.55 per IQR increase [14.46 μg/m3]), and associations were elevated for nonsmokers, aspirin nonusers, and those without a history of high cholesterol. However, we observed no evidence of a positive association between short-term exposure to PM and hemorrhagic stroke or between PM2.5 and ischemic stroke in this cohort. CONCLUSIONS: Our study provides evidence that ambient PM10 may be associated with higher risk of ischemic stroke and highlights that ischemic and hemorrhagic strokes are heterogeneous outcomes that should be treated as such in analyses related to air pollution.

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.