scholarly journals Relationship between season of birth, temperature exposure, and later life wellbeing

2017 ◽  
Vol 114 (51) ◽  
pp. 13447-13452 ◽  
Author(s):  
Adam Isen ◽  
Maya Rossin-Slater ◽  
Reed Walker
Keyword(s):  
Temperature Sensitivity ◽  
Later Life ◽  
First Trimester ◽  
The United States ◽  
In Utero ◽  
Weather Data ◽  
Long Run ◽  
Daily Weather Data ◽  
Different Temperatures ◽  
Annual Earnings

We study how exposure to extreme temperatures in early periods of child development is related to adult economic outcomes measured 30 y later. Our analysis uses administrative earnings records for over 12 million individuals born in the United States between 1969 and 1977, linked to fine-scale, daily weather data and location and date of birth. We calculate the length of time each individual is exposed to different temperatures in utero and in early childhood, and we estimate flexible regression models that allow for nonlinearities in the relationship between temperature and long-run outcomes. We find that an extra day with mean temperatures above 32 °C in utero and in the first year after birth is associated with a 0.1% reduction in adult annual earnings at age 30. Temperature sensitivity is evident in multiple periods of early development, ranging from the first trimester of gestation to age 6–12 mo. We observe that household air-conditioning adoption, which increased dramatically over the time period studied, mitigates nearly all of the estimated temperature sensitivity.

scholarly journals Impact of Extreme Weather on Healthcare Utilization by People with HIV in Metropolitan Miami

2021 ◽  
Vol 18 (5) ◽  
pp. 2442
Author(s):  
Daniel Samano ◽  
Shubhayu Saha ◽  
Taylor Corbin Kot ◽  
JoNell E. Potter ◽  
Lunthita M. Duthely
Keyword(s):  
Relative Risk ◽  
The United States ◽  
Extreme Weather ◽  
South Florida ◽  
Heat Index ◽  
Extreme Weather Events ◽  
Weather Data ◽  
Steady Increase ◽  
Daily Weather Data ◽  
The Impact

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990–2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017–2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients’ ‘no-show’ status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of ‘no-show’ was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population’s utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.

scholarly journals Evaluation of the Ryegrass Stem Rust Model STEMRUST_G and Its Implementation as a Decision Aid

2015 ◽  
Vol 105 (1) ◽  
pp. 35-44 ◽  
Author(s):  
W. F. Pfender ◽  
L. B. Coop ◽  
S. G. Seguin ◽  
M. E. Mellbye ◽  
G. A. Gingrich ◽  
...  
Keyword(s):  
Disease Management ◽  
Pacific Northwest ◽  
Stem Rust ◽  
Decision Aid ◽  
Decision Aids ◽  
Weather Conditions ◽  
The United States ◽  
Weather Data ◽  
Daily Weather Data ◽  
Epidemic Development

STEMRUST_G, a simulation model for epidemics of stem rust in perennial ryegrass grown to maturity as a seed crop, was validated for use as a heuristic tool and as a decision aid for disease management with fungicides. Multistage validation had been used in model creation by incorporating previously validated submodels for infection, latent period duration, sporulation, fungicide effects, and plant growth. Validation of the complete model was by comparison of model output with observed disease severities in 35 epidemics at nine location-years in the Pacific Northwest of the United States. We judge the model acceptable for its purposes, based on several tests. Graphs of modeled disease progress were generally congruent with plotted disease severity observations. There was negligible average bias in the 570 modeled-versus-observed comparisons across all data, although there was large variance in size of the deviances. Modeled severities were accurate in >80% of the comparisons, where accuracy is defined as the modeled value being within twice the 95% confidence interval of the observed value, within ± 1 day of the observation date. An interactive website was created to produce disease estimates by running STEMRUST_G with user-supplied disease scouting information and automated daily weather data inputs from field sites. The model and decision aid supplement disease managers' information by estimating the level of latent (invisible) and expressed disease since the last scouting observation, given season-long weather conditions up to the present, and it estimates effects of fungicides on epidemic development. In additional large-plot experiments conducted in grower fields, the decision aid produced disease management outcomes (management cost and seed yield) as good as or better than the growers' standard practice. In future, STEMRUST_G could be modified to create similar models and decision aids for stem rust of wheat and barley, after additional experiments to determine appropriate parameters for the disease in these small-grain hosts.

scholarly journals Evaluation of Various Methods for Estimating Global Solar Radiation in the Southeastern United States

2012 ◽  
Vol 51 (5) ◽  
pp. 972-985 ◽  
Author(s):  
Prem Woli ◽  
Joel O. Paz
Keyword(s):  
United States ◽  
Solar Radiation ◽  
Southeastern United States ◽  
Global Solar Radiation ◽  
The United States ◽  
Data Availability ◽  
The Other ◽  
Weather Data ◽  
Temperature And Precipitation ◽  
Daily Weather Data

AbstractGlobal solar radiation Rg is an important input for crop models to simulate crop responses. Because the scarcity of long and continuous records of Rg is a serious limitation in many countries, Rg is estimated using models. For crop-model application, empirical Rg models that use commonly measured meteorological variables, such as temperature and precipitation, are generally preferred. Although a large number of models of this kind exist, few have been evaluated for conditions in the United States. This study evaluated the performances of 16 empirical, temperature- and/or precipitation-based Rg models for the southeastern United States. By taking into account spatial distribution and data availability, 30 locations in the region were selected and their daily weather data spanning eight years obtained. One-half of the data was used for calibrating the models, and the other half was used for evaluation. For each model, location-specific parameter values were estimated through regressions. Models were evaluated for each location using the root-mean-square error and the modeling efficiency as goodness-of-fit measures. Among the models that use temperature or precipitation as the input variable, the Mavromatis model showed the best performance. The piecewise linear regression–based Wu et al. model (WP) performed best not only among the models that use both temperature and precipitation but also among the 16 models evaluated, mainly because it has separate relationships for low and high radiation levels. The modeling efficiency of WP was from ~5% to more than 100% greater than those of the other models, depending on models and locations.

The Impact of Monetary and Fiscal Policies on the Stock Market in the United States (U.S); Evidence from Linear ARDL Framework

2020 ◽  
Vol 11 (1) ◽  
pp. 132-132
Author(s):  
Aref Emamian
Keyword(s):  
United States ◽  
Stock Market ◽  
The United States ◽  
Real Effective Exchange Rate ◽  
Annual Data ◽  
Fiscal Policies ◽  
Long Run ◽  
The Us ◽  
Short Run ◽  
The Impact

This study examines the impact of monetary and fiscal policies on the stock market in the United States (US), were used. By employing the method of Autoregressive Distributed Lags (ARDL) developed by Pesaran et al. (2001). Annual data from the Federal Reserve, World Bank, and International Monetary Fund, from 1986 to 2017 pertaining to the American economy, the results show that both policies play a significant role in the stock market. We find a significant positive effect of real Gross Domestic Product and the interest rate on the US stock market in the long run and significant negative relationship effect of Consumer Price Index (CPI) and broad money on the US stock market both in the short run and long run. On the other hand, this study only could support the significant positive impact of tax revenue and significant negative impact of real effective exchange rate on the US stock market in the short run while in the long run are insignificant. Keywords: ARDL, monetary policy, fiscal policy, stock market, United States

China's Western Horizon

2020 ◽  
Author(s):  
Daniel S. Markey
Keyword(s):  
Political Influence ◽  
The United States ◽  
The Political ◽  
Regional Politics ◽  
National Wealth ◽  
Long Run ◽  
Political Implications ◽  
Foreign Policies ◽  
Belt And Road ◽  
Infrastructure Investments

This book explains how China’s new foreign policies like the vaunted “Belt and Road” Initiative are being shaped by local and regional politics outside China and assesses the political implications of these developments for Eurasia and the United States. It depicts the ways that President Xi Jinping’s China is zealously transforming its national wealth and economic power into tools of global political influence and details these developments in South Asia, Central Asia, and the Middle East. Drawing from extensive interviews, travels, and historical research, it describes how perceptions of China vary widely within states like Pakistan, Kazakhstan, and Iran. Eurasia’s powerful and privileged groups often expect to profit from their connections to China, while others fear commercial and political losses. Similarly, statesmen across Eurasia are scrambling to harness China’s energy purchases, arms sales, and infrastructure investments as a means to outdo their strategic competitors, like India and Saudi Arabia, while negotiating relations with Russia and America. The book finds that, on balance, China’s deepening involvement will play to the advantage of regional strongmen and exacerbate the political tensions within and among Eurasian states. To make the most of America’s limited influence along China’s western horizon (and elsewhere), it argues that US policymakers should pursue a selective and localized strategy to serve America’s aims in Eurasia and to better compete with China over the long run.

scholarly journals Distribution and incidence of viruses in Irish seed potato crops

2015 ◽  
Vol 54 (2) ◽  
pp. 98-106 ◽  
Author(s):  
F. Hutton ◽  
J.H. Spink ◽  
D. Griffin ◽  
S. Kildea ◽  
D. Bonner ◽  
...  
Keyword(s):  
Potato Virus ◽  
Significant Proportion ◽  
Potato Production ◽  
Weather Data ◽  
Management Approach ◽  
Potato Seed ◽  
Virus Diseases ◽  
Aphid Control ◽  
Daily Weather Data ◽  
Potato Crops

Abstract Virus diseases are of key importance in potato production and in particular for the production of disease-free potato seed. However, there is little known about the frequency and distribution of potato virus diseases in Ireland. Despite a large number of samples being tested each year, the data has never been collated either within or across years. Information from all known potato virus testing carried out in the years 2006–2012 by the Department of Agriculture Food and Marine was collated to give an indication of the distribution and incidence of potato virus in Ireland. It was found that there was significant variation between regions, varieties, years and seed classes. A definition of daily weather data suitable for aphid flight was developed, which accounted for a significant proportion of the variation in virus incidence between years. This use of weather data to predict virus risk could be developed to form the basis of an integrated pest management approach for aphid control in Irish potato crops.

scholarly journals Sexuality in Later Life and Mental Health Among Older Black Gay Men

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 313-314
Author(s):  
Darlingtina Esiaka ◽  
Alice Cheng ◽  
Candidus Nwakasi
Keyword(s):  
Mental Health ◽  
Gay Men ◽  
Later Life ◽  
The United States ◽  
Mental Wellbeing ◽  
Self Identity ◽  
Sexual Identities ◽  
Age Related ◽  
Wide Range ◽  
Black Gay Men

Abstract Self-acknowledgement and integration of racial and sexual identities are significant to one’s overall sense of identity because of their implications for mental health and wellbeing. These issues are important as one ages because older people experience a wide range of factors that add layers to their ability to (re)integrate subsets of their identity into their overall self-identity such as age and age-related disabilities. This study examined the intersection of race and sexual identities on overall health status in older Black gay men, a demographic group that has historically received less attention. Data from the Social Justice Sexuality (SJS) survey of LGBTQ+ people of color which occurred over a 12-month period in the United States were analyzed. Participants (N=160), 50 years and over, responded to questions about their sexuality, social identity, family dynamics, community connection and engagement, and mental and physical health. Results show an association of mental wellbeing with racial and sexual identities. Further, results show that a strong sense of connection to other sexual minorities is positively associated with mental health in older Black gay men. We discuss the implication of findings for mental health interventions targeting this gendered population.

scholarly journals Association between Genetic Variants in NOS2 and TNF Genes with Congenital Zika Syndrome and Severe Microcephaly

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 325
Author(s):  
Julia A. Gomes ◽  
Eduarda Sgarioni ◽  
Juliano A. Boquett ◽  
Ana Cláudia P. Terças-Trettel ◽  
Juliana H. da Silva ◽  
...  
Keyword(s):  
Risk Factors ◽  
Zika Virus ◽  
Genetic Variants ◽  
Educational Level ◽  
Congenital Anomalies ◽  
Family Income ◽  
First Trimester ◽  
In Utero ◽  
Zikv Infection ◽  
Congenital Zika Syndrome

Zika virus (ZIKV) causes Congenital Zika Syndrome (CZS) in individuals exposed prenatally. Here, we investigated polymorphisms in VEGFA, PTGS2, NOS3, TNF, and NOS2 genes as risk factors to CZS. Forty children with CZS and forty-eight children who were in utero exposed to ZIKV infection, but born without congenital anomalies, were evaluated. Children with CZS were predominantly infected by ZIKV in the first trimester (p < 0.001) and had mothers with lower educational level (p < 0.001) and family income (p < 0.001). We found higher risk of CZS due the allele rs2297518[A] of NOS2 (OR = 2.28, CI 95% 1.17–4.50, p = 0.015). T allele and TT/CT genotypes of the TNF rs1799724 and haplotypes associated with higher expression of TNF were more prevalent in children with CZS and severe microcephaly (p = 0.029, p = 0.041 and p = 0.030, respectively). Our findings showed higher risk of CZS due ZIKV infection in the first trimester and suggested that polymorphisms in NOS2 and TNF genes affect the risk of CZS and severe microcephaly.

scholarly journals Debt Relief and Debtor Outcomes: Measuring the Effects of Consumer Bankruptcy Protection

2015 ◽  
Vol 105 (3) ◽  
pp. 1272-1311 ◽  
Author(s):  
Will Dobbie ◽  
Jae Song
Keyword(s):  
United States ◽  
Social Insurance ◽  
The United States ◽  
Debt Relief ◽  
Random Assignment ◽  
Percentage Points ◽  
Consumer Bankruptcy ◽  
Annual Earnings ◽  
The Impact

Consumer bankruptcy is one of the largest social insurance programs in the United States, but little is known about its impact on debtors. We use 500,000 bankruptcy filings matched to administrative tax and foreclosure data to estimate the impact of Chapter 13 bankruptcy protection on subsequent outcomes. Exploiting the random assignment of bankruptcy filings to judges, we find that Chapter 13 protection increases annual earnings by $5,562, decreases five-year mortality by 1.2 percentage points, and decreases five-year foreclo-sure rates by 19.1 percentage points. These results come primarily from the deterioration of outcomes among dismissed filers, not gains by granted filers. (JEL D14, I12, J22, J31, K35)

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

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