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Alcoholism is a common disease resulting from the complex interaction of genetic, social, and environmental factors. Interest in the high heritability of alcoholism has resulted in many studies of how [...]

The article looks at a study which examine association of in vivo g-aminobutyric acid (GABA) levels during an respiratory syncytial virus (RSV) acute respiratory infections (ARI) in infancy with illness severity and subsequent risk of childhood asthma. It mentions pathophysiology of asthma known about the effect of this neurotransmitter on RSV-related outcomes in humans. It also mentions illness by reverse-transcription polymerase chain reaction, rapid antigen test.

Objective: To examine perceptions, behaviors, and impacts surrounding COVID-19 early in the pandemic response. Materials and methods: A cross-sectional survey of 1,030 U.S. adults was administered on March 31st, 2020. This survey examined attitudes toward media, government, and community responses to COVID-19 by political ideology and sociodemographic factors. Knowledge, anxieties, and impacts of COVID-19 were also assessed. Results: Conservatives were more likely to report that COVID-19 was receiving too much media coverage and people were generally overreacting; liberals were more likely to report the government had not done enough in response to the pandemic. Females and those with lower income experienced more COVID-19 related economic anxieties. Those working and with children at home reported higher social, home, and work disruption. Social distancing behaviors were more common among liberals and were associated with increases in depressive symptoms. General knowledge about COVID-19 was widely exhibited across the sample, however, Black and Hispanic respondents were less likely to correctly answer questions about the availability of a vaccine and modes of transmission. Conclusions: Public health experts should consider the political climate in crafting messaging that appeals to the values of those across the political spectrum. Research on the COVID-19 pandemic should continue to monitor the effects of social distancing on mental health and among vulnerable populations. [ABSTRACT FROM AUTHOR]

Low atmospheric pressure may increase depression and suicide through inducing hypoxia. Previous studies have not evaluated the geographic variation of this relationship across the United States. Analyses were based on three groupings of age-adjusted completed suicide rates (all suicide, firearm-related suicide, non-firearm-related suicide) from 2286 counties in the United States. Multiple regression was used to determine the overall relationship between atmospheric pressure and completed suicide rates. Geographically weighted regression (GWR) models were used to obtain local coefficient estimates. A negative correlation between atmospheric pressure and completed suicide rates was observed for all three suicide groupings (p-value <0.0001). Significant, negative GWR coefficient estimates were located in the West and Northeast for the all suicides and firearm-related suicides, and in the Midwest for non-firearm-related suicides. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to investigate disparities in mental healthcare delivery in American Indian/Alaska Native populations from three perspectives: public health, legal policy and mental healthcare and provide evidence-based recommendations toward reducing those disparities. Data on mental health funding to tribes were obtained from the Substance Abuse and Mental Health Services Administration. As a result of analysis of these data, vital statistics and current literature, we propose three recommendations to reduce mental health disparities. First, where possible, increase mental health funding opportunities for federally-recognized tribes. Second, model funding practices on principles of tribal self-determination. Finally, support diverse interventions that are culturally-based and culturally-appropriate. [ABSTRACT FROM AUTHOR]

Traffic-related air pollution in urban areas contributes significantly to commuters’ daily PM2.5 exposures, but varies widely depending on mode of commuting. To date, studies show conflicting results for PM2.5 exposures based on mode of commuting, and few studies compare multiple modes of transportation simultaneously along a common route, making inter-modal comparisons difficult. In this study, we examined breathing zone PM2.5 exposures for six different modes of commuting (bicycle, walking, driving with windows open and closed, bus, and light-rail train) simultaneously on a single 2.7 km (1.68 mile) arterial urban route in Salt Lake City, Utah (USA) during peak “rush hour” times. Using previously published minute ventilation rates, we estimated the inhaled dose and exposure rate for each mode of commuting. Mean PM2.5 concentrations ranged from 5.20 μg/m3 for driving with windows closed to 15.21 μg/m3 for driving with windows open. The estimated inhaled doses over the 2.7 km route were 6.83 μg for walking, 2.78 μg for cycling, 1.28 μg for light-rail train, 1.24 μg for driving with windows open, 1.23 μg for bus, and 0.32 μg for driving with windows closed. Similarly, the exposure rates were highest for cycling (18.0 μg/hr) and walking (16.8 μg/hr), and lowest for driving with windows closed (3.7 μg/hr). Our findings support previous studies showing that active commuters receive a greater PM2.5 dose and have higher rates of exposure than commuters using automobiles or public transportation. Our findings also support previous studies showing that driving with windows closed is protective against traffic-related PM2.5 exposure. [ABSTRACT FROM AUTHOR]

Rates of Sudden Unexplained Infant Death (SUID), bronchiolitis, and central apnea increase in winter in temperate climates. Though associations between these three conditions are suggested, more work is required to establish if there is a causal pathway linking bronchiolitis to SUID through inducing central apnea. Utilizing a large population-based cohort of infants studied over a 20-year period (n = 834,595, from birth years 1989–2009)), we analyzed ecological associations between timing of SUID cases, bronchiolitis, and apnea healthcare visits. Data were analyzed between 2013 and 2015. We used a Cox Proportional Hazards model to analyze possible interactions between maternal smoking and maternal asthma with infant bronchiolitis on time to SUID. SUID and bronchiolitis both occurred more frequently in winter. An increase in bronchiolitis clinical visits occurred within a few days prior to apnea visits. We found a temporal relationship between infant bronchiolitis and apnea. In contrast, no peak in SUID cases was seen during peaks of bronchiolitis. Among those without any bronchiolitis visits, maternal smoking was associated with an increased risk of SUID: Hazard Ratio (HR) of 2.38 (95% CI: 2.11, 2.67, p-value <0.001). Maternal asthma was associated with an increased risk of SUID among infants with at least one bronchiolitis visit: HR of 2.40 (95% CI: 1.04, 5.54, p-value = 0.04). Consistent trends between bronchiolitis, apnea, and SUID were not established due to small numbers of SUID cases. However, interaction analysis revealed potential differential associations of bronchiolitis and SUID by maternal smoking, maternal asthma status. [ABSTRACT FROM AUTHOR]

Continued development of personal air pollution monitors is rapidly improving government and research capabilities for data collection. In this study, we tested the feasibility of using GPS-enabled personal exposure monitors to collect personal exposure readings and short-term daily PM2.5measures at 15 fixed locations throughout a community. The goals were to determine the accuracy of fixed-location monitoring for approximating individual exposures compared to a centralized outdoor air pollution monitor, and to test the utility of two different personal monitors, the RTI MicroPEM V3.2 and TSI SidePak AM510. For personal samples, 24-hr mean PM2.5concentrations were 6.93 μg/m3(stderr = 0.15) and 8.47 μg/m3(stderr = 0.10) for the MicroPEM and SidePak, respectively. Based on time–activity patterns from participant journals, exposures were highest while participants were outdoors (MicroPEM = 7.61 µg/m3, stderr = 1.08, SidePak = 11.85 µg/m3, stderr = 0.83) or in restaurants (MicroPEM = 7.48 µg/m3, stderr = 0.39, SidePak = 24.93 µg/m3, stderr = 0.82), and lowest when participants were exercising indoors (MicroPEM = 4.78 µg/m3, stderr = 0.23, SidePak = 5.63 µg/m3, stderr = 0.08). Mean PM2.5at the 15 fixed locations, as measured by the SidePak, ranged from 4.71 µg/m3(stderr = 0.23) to 12.38 µg/m3(stderr = 0.45). By comparison, mean 24-h PM2.5measured at the centralized outdoor monitor ranged from 2.7 to 6.7 µg/m3during the study period. The range of average PM2.5exposure levels estimated for each participant using the interpolated fixed-location data was 2.83 to 19.26 µg/m3(mean = 8.3, stderr = 1.4). These estimated levels were compared with average exposure from personal samples. The fixed-location monitoring strategy was useful in identifying high air pollution microclimates throughout the county. For 7 of 10 subjects, the fixed-location monitoring strategy more closely approximated individuals’ 24-hr breathing zone exposures than did the centralized outdoor monitor. Highlights are: Individual PM2.5exposure levels vary extensively by activity, location and time of day; fixed-location sampling more closely approximated individual exposures than a centralized outdoor monitor; and small, personal exposure monitors provide added utility for individuals, researchers, and public health professionals seeking to more accurately identify air pollution microclimates. Implications: Personal air pollution monitoring technology is advancing rapidly. Currently, personal monitors are primarily used in research settings, but could they also support government networks of centralized outdoor monitors? In this study, we found differences in performance and practicality for two personal monitors in different monitoring scenarios. We also found that personal monitors used to collect outdoor area samples were effective at finding pollution microclimates, and more closely approximated actual individual exposure than a central monitor. Though more research is needed, there is strong potential that personal exposure monitors can improve existing monitoring networks. [ABSTRACT FROM PUBLISHER]

Background: Non-Hodgkin lymphoma (NHL) is an enigmatic disease with few known risk factors. Spatio-temporal epidemiologic analyses have the potential to reveal patterns that may give clues to new risk factors worthy of investigation. We sought to investigate clusters of NHL through space and time based on life course residential histories. Methods: We used residential histories from a population-based NHL case-control study of 1300 cases and 1044 controls with recruitment centers in Iowa, Detroit, Seattle, and Los Angeles, and diagnosed in 1998-2000. Novel methods for cluster detection allowing for residential mobility, called Q-statistics, were used to quantify nearest neighbor relationships through space and time over the life course to identify cancer clusters. Analyses were performed on all cases together and on two subgroups of NHL: Diffuse large B-cell lymphoma and follicular lymphoma. These more homogenous subgroups of cases might have a more common etiology that could potentially be detected in cluster analysis. Based on simulation studies designed to help account for multiple testing across space and through time, we required at least four significant cases nearby one another to declare a region a potential cluster, along with confirmatory analyses using spatial-only scanning windows (SaTScan). Results: Evidence of a small cluster in southeastern Oakland County, MI was suggested using residences 10-18 years prior to diagnosis, and confirmed by SaTScan in a time-slice analysis 20 years prior to diagnosis, when all cases were included in the analysis. Consistent evidence of clusters was not seen in the two histologic subgroups. Conclusions: Suggestive evidence of a small space-time cluster in southeastern Oakland County, MI was detected in this NHL case-control study in the USA. [ABSTRACT FROM AUTHOR]

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population. [ABSTRACT FROM AUTHOR]

Indoor and outdoor air pollution is known to contribute to increased lung cancer incidence. This study is the first to address the contribution of home heating fuel and geographical course particulate matter (PM10) concentrations to lung cancer rates in New Hampshire, USA. First, Pearson correlation analysis and geographically weighted regression were used to investigate spatial relationships between outdoor PM10 and lung cancer rates. While the aforementioned analyses did not indicate a significant contribution of PM10 to lung cancer in the state, there was a trend towards a significant association in the northern and southwestern regions of the state. Second, case-control data were used to estimate the contributions of indoor pollution and secondhand smoke to the risk of lung cancer with adjustment for confounders. Increased risk was found among those who used wood or coal to heat their homes for more than 10 winters before the age of 18, with a significant increase in risk per winter. Resulting data suggest that further investigation of the relationship between heating-related air pollution levels and lung cancer risk is needed. [ABSTRACT FROM AUTHOR]

Genetic structure due to ancestry has been well documented among many divergent human populations. However, the ability to associate ancestry with genetic substructure without using supervised clustering has not been explored in more presumably homogeneous and admixed US populations. The goal of this study was to determine if genetic structure could be detected in a United States population from a single state where the individuals have mixed European ancestry. Using Bayesian clustering with a set of 960 single nucleotide polymorphisms (SNPs) we found evidence of population stratification in 864 individuals from New Hampshire that can be used to differentiate the population into six distinct genetic subgroups. We then correlated self-reported ancestry of the individuals with the Bayesian clustering results. Finnish and Russian/Polish/ Lithuanian ancestries were most notably found to be associated with genetic substructure. The ancestral results were further explained and substantiated using New Hampshire census data from 1870 to 1930 when the largest waves of European immigrants came to the area. We also discerned distinct patterns of linkage disequilibrium (LD) between the genetic groups in the growth hormone receptor gene (GHR). To our knowledge, this is the first time such an investigation has uncovered a strong link between genetic structure and ancestry in what would otherwise be considered a homogenous US population. [ABSTRACT FROM AUTHOR]

Previous studies have found evidence of viral interference between seasonal respiratory viruses. Using laboratory-confirmed data from a Utah-based healthcare provider, Intermountain Health Care, we analyzed the time-specific patterns of respiratory syncytial virus (RSV), influenza A, influenza B, human metapneumovirus, rhinovirus, and enterovirus circulation from 2004 to 2018, using descriptive methods and wavelet analysis (n = 89,462) on a local level. The results showed that RSV virus dynamics in Utah were the most consistent of any of the viruses studied, and that the other seasonal viruses were generally in synchrony with RSV, except for enterovirus (which mostly occurs late summer to early fall) and influenza A and B during pandemic years. [ABSTRACT FROM AUTHOR]

With the introduction of fentanyl to illegal markets in 2013 and an overall rise in rates of synthetic opioid use, opioid-related deaths have increased significantly. A similar trend has been observed for sexually transmitted infections, homicides, and poor mental health outcomes. In this paper, we explore the spatiotemporal relationship between opioid death rates and sexually transmitted infection (STI) rates in counties from the Northeast region of the United States between the years 2012-2017. We hypothesized that rates for gonorrhea, chlamydia, and human immunodeficiency virus (HIV) would all be positively associated with opioid death rates and that there would be a similar association between the STI rates and later time periods relative to earlier time periods. A negative binomial mixed-effects regression model was employed to assess these associations. Contrary to the study hypothesis, opioid death rates were not found to be significantly associated with the STI rates after accounting for other demographic and socioeconomic variables, with the exception of opioid deaths and gonorrhea in urban counties. Additionally, the regression demonstrated a significant association between infection rate and time period beyond the included socioeconomic variables and opioid deaths. Overall, this study indicates that declining sexual health outcomes may parallel rising opioid death, though both trends may be explained by similar underlying factors related to time period.

Hierarchical clustering is frequently used for grouping results in expression or haplotype analyses. These methods can elucidate patterns between measures that can then be applied to discerning their validity in discriminating between experimental conditions. Here a hierarchical clustering method is used to analyze the results of an imaging genetics study using multiple brain morphology and cognitive testing endpoints for older adults with amnestic mild cognitive impairment (MCI) or cognitive complaints (CC) compared to healthy controls (HC). The single nucleotide polymorphisms (SNPs) are a subset of those included on a larger array that are found in a reported Alzheimer's disease (AD) and neurodegeneration pathway. The results indicate that genetic models within the endpoints cluster together, while there are 4 distinct sets of SNPs that differentiate between the endpoints, with most significant results associated with morphology endpoints rather than cognitive testing of patients' reported symptoms. The genes found in at least one cluster are ABCB1, APBA1, BACE1, BACE2, BCL2, BCL2L1, CASP7, CHAT, CST3, DRD3, DRD5, IL6, LRP1, NAT1, and PSEN2. The greater associations with morphology endpoints suggests that changes in brain structure can be influenced by an individual's genetic background in the absence of dementia and in some cases (Cognitive Complaints group) even without those effects necessarily being detectable on commonly used clinical tests of cognition. The results are consistent with polygenic influences on early neurodegenerative changes and demonstrate the effectiveness of hierarchical clustering in identifying genetic associations among multiple related phenotypic endpoints., ((c) 2010 Wiley-Liss, Inc.)