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Actors are often asked by directors to "play" with the material they are given in an attempt to create new artistic choices free of inhibitions. While proposed with no ill-intent, this request has the potential to create unwanted activations of an actor's sympathetic nervous system due to the removal of familiar rehearsal practices. Removing this ask from a director's vocabulary lessens the chance of negative interactions with an actor’s boundaries, but may leave other members of the creative team and actors may be left wanting more. By creating theatrical play grounded in the principles of Dr. Stephen W. Porges' Polyvagal Theory, potential trauma responses can be accounted for while allowing for an artistically fulfilling and consensual rehearsal process.

Temperature-related mortality is the leading cause of weather-related deaths in the United States. Herein, we explore the effect of air masses (AMs) - a relatively novel and holistic measure of environmental conditions - on human mortality across 61 cities in the United States. Geographic and seasonal differences in the effects of each AM on deseasonalized and detrended anomalous lagged mortality are examined using simple descriptive statistics, one-way analyses of variance, relative risks of excess mortality, and regression-based artificial neural network (ANN) models. Results show that AMs are significantly related to anomalous mortality in most US cities, and in most seasons. Of note, two of the three cool AMs (Cool and Dry-Cool) each show a strong, but delayed mortality response in all seasons, with peak mortality 2 to 4 days after they occur, with the Dry-Cool AM having nearly a 15% increased risk of excess mortality. Humid-Warm (HW) air masses are associated with increases in deaths in all seasons 0 to 1 days after they occur. In most seasons, these near-term mortality increases are offset by reduced mortality for 1-2 weeks afterwards; however, in summer, no such reduction is noted. The Warm and Dry-Warm AMs show slightly longer periods of increased mortality, albeit slightly less intensely as compared with HW, but with a similar lag structure by season. Meanwhile, the most seasonally consistent results are with transitional weather, whereby passing cold fronts are associated with a significant decrease in mortality 1 day after they occur, while warm fronts are associated with significant increases in mortality at that same lag time. Finally, ANN modeling reveals that AM-mortality relationships gleaned from a combined meta-analysis can actually lead to more skillful modeling of these relationships than models trained on some individual cities, especially in the cities where such relationships might be masked due to low average daily mortality., (© 2024. The Author(s).)

As studies begin to have more success uncovering the relationships between atmospheric conditions and pain, weather-based pain forecasting becomes more of a reality. In this study, a survey was used to determine if people living with migraines and/or other pain-related conditions are receptive to weather-based pain forecasts. Moreover, we wished to identify whether these forecasts actually impact the decision-making of those who use them. Survey respondents were generally eager to use these novel forecasts. Furthermore, when provided with different scenarios involving weather-based pain forecasts, the respondents' actions were altered. When a hypothetical forecast indicated that the weather was conducive to migraines or other types of pain, many indicated that they would likely take preventative measures (e.g., medication). Additionally, respondents were less likely to continue with a planned activity, regardless of length, as forecast severity increased. The results from this survey highlight the importance of developing and improving weather-based pain forecasting., (© 2023. The Author(s) under exclusive licence to International Society of Biometeorology.)

Background: Climate change is projected to result in increased heat events and decreased cold events. This will substantially impact human health, particularly when compounded with demographic change. This study employed the Spatial Synoptic Classification (SSC) to categorize daily weather into one of seven types. Here we estimated future mortality due to extremely hot and cold weather types under different climate change scenarios for one southern (Stockholm) and one northern (Jämtland) Swedish region., Methods: Time-series Poisson regression with distributed lags was used to assess the relationship between extremely hot and cold weather events and daily deaths in the population above 65 years, with cumulative effects (6 days in summer, 28 days in winter), 1991 to 2014. A global climate model (MPI-M-MPI-ESM-LR) and two climate change scenarios (RCP 4.5 and 8.5) were used to project the occurrence of hot and cold days from 2031 to 2070. Place-specific projected mortality was calculated to derive attributable numbers and attributable fractions (AF) of heat- and cold-related deaths., Results: In Stockholm, for the RCP 4.5 scenario, the mean number of annual deaths attributed to heat increased from 48.7 (CI 32.2-64.2; AF = 0.68%) in 2031-2040 to 90.2 (56.7-120.5; AF = 0.97%) in 2061-2070, respectively. For RCP 8.5, heat-related deaths increased more drastically from 52.1 (33.6-69.7; AF = 0.72%) to 126.4 (68.7-175.8; AF = 1.36%) between the first and the last decade. Cold-related deaths slightly increased over the projected period in both scenarios. In Jämtland, projections showed a small decrease in cold-related deaths but no change in heat-related mortality., Conclusions: In rural northern region of Sweden, a decrease of cold-related deaths represents the dominant trend. In urban southern locations, on the other hand, an increase of heat-related mortality is to be expected. With an increasing elderly population, heat-related mortality will outweigh cold-related mortality at least under the RCP 8.5 scenario, requiring societal adaptation measures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State., Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees., Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9-15.6%), population density (3.3-16.1%), per capita income (2.3-10.7%), and the density of public infrastructure (0.8-8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3-27.9%) and those with limited English (2.2-8.1%), the percent of sandy soil (6.5-11.8%), and average soil temperature (3.0-15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status., Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization., Competing Interests: Conflict of interest All authors declare they have no actual or potential competing financial interest.

Bodily pain plagues populations across the globe. Past studies have discovered some links between synoptic weather types and different kinds of pain. These relationships are essential as they can aide in treatment and potentially prevention of pain. In this study, the role of geographical characteristics on the relationships between synoptic weather type and pain were looked at. North Carolina was separated into three geographic sections: Appalachian Mountains, Piedmont Plateau, and Coastal Plain. Over a 7-year period, synoptic weather types and emergency department (ED) visits for various kinds of pain (migraine, fibromyalgia, rheumatoid arthritis, osteoarthritis, and general back pain) were collected. Bootstrapped confidence intervals of the mean number of population-adjusted ED visit rates (per 100,000 persons), for the different synoptic weather types, were compared across the different geographic regions. In the plateau region, Moist Tropical and Moist Moderate weather types were often linked to the highest rates of ED visits, while Polar weather types were frequently associated with the fewest visits. The mountainous portion of the state displayed similar patterns between synoptic weather types and the different forms of pain, with migraine and fibromyalgia being the exceptions. Few statistically significant relationships were noted for the coastal region., (© 2021. ISB.)

Background: Exposure to high and low ambient temperatures is associated with morbidity and mortality across the globe. Most of these studies assessing the effects of non-optimum temperatures on health and have been conducted in the developed world, whereas in India, the limited evidence on ambient temperature and health risks and has focused mostly on the effects of heat waves. Here we quantify short term association between all temperatures and mortality in urban Pune, India., Methods: We applied a time series regression model to derive temperature-mortality associations based on daily mean temperature and all-cause mortality records of Pune city from year January 2004 to December 2012. We estimated high and low temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model (DLNM). We calculated temperature attributable mortality fractions for total heat and total cold., Findings: The analysis provides estimates of the total mortality burden attributable to ambient temperature. Overall, 6∙5% [95%CI 1.76-11∙43] of deaths registered in the observational period were attributed to non-optimal temperatures, cold effect was greater 5.72% [95%CI 0∙70-10∙06] than heat 0∙84% [0∙35-1∙34]. The gender stratified analysis revealed that the highest burden among men both for heat and cold., Conclusion: Non-optimal temperatures are associated with a substantial mortality burden. Our findings could benefit national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately due to climate change., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Background/objective: Research suggests gestational exposure to particulate matter ≤2.5 μm (PM 2.5 ) and extreme heat may independently increase risk of birth defects. We investigated whether duration of gestational extreme heat exposure modifies associations between PM 2.5 exposure and specific congenital heart defects (CHDs). We also explored nonlinear exposure-outcome relationships., Methods: We identified CHD case children (n = 2824) and non-malformed live-birth control children (n = 4033) from pregnancies ending between 1999 and 2007 in the National Birth Defects Prevention Study, a U.S. population-based multicenter case-control study. We assigned mothers 6-week averages of PM 2.5 exposure during the cardiac critical period (postconceptional weeks 3-8) using the closest monitor within 50 km of maternal residence. We assigned a count of extreme heat days (EHDs, days above the 90th percentile of daily maximum temperature for year, season, and weather station) during this period using the closest weather station. Using generalized additive models, we explored logit-nonlinear exposure-outcome relationships, concluding logistic models were reasonable. We estimated joint effects of PM 2.5 and EHDs on six CHDs using logistic regression models adjusted for mean dewpoint and maternal age, education, and race/ethnicity. We assessed multiplicative and additive effect modification., Results: Conditional on the highest observed EHD count (15) and at least one critical period day during spring/summer, each 5 μg/m 3 increase in average PM 2.5 exposure was significantly associated with perimembranous ventricular septal defects (VSDpm; OR: 1.54 [95% CI: 1.01, 2.41]). High EHD counts (8+) in the same population were positively, but non-significantly, associated with both overall septal defects and VSDpm. Null or inverse associations were observed for lower EHD counts. Multiplicative and additive effect modification estimates were consistently positive in all septal models., Conclusions: Results provide limited evidence that duration of extreme heat exposure modifies the PM 2.5 -septal defects relationship. Future research with enhanced exposure assessment and modeling techniques could clarify these relationships., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: There is little work in assessing the impact of storm events combined with power outage (PO). In this study, we evaluated the individual and synergistic impacts of wind events and PO on overall and subtypes of injuries in New York State (NYS) and by demographics., Methods: The emergency department (ED) visit data were obtained from the NYS Department of Health from November-April 2005-2013 to identify injury cases, length of stay and care costs. Wind event was defined according to high wind, strong wind or thunderstorm wind defined by NOAA. PO occurrence was defined when PO coverage exceeded the 50th percentile of its distribution. By comparing non-event days, we used distributed lag nonlinear models to evaluate the impacts of wind events, PO, and their combined effect on injuries during the cold season over a 0-3-day lag period, while controlling for time-varying confounders. The differences in critical care indicators between event and non-event days were also evaluated., Results: Overall injuries ED visits (16,628,812) significantly increased during the wind events (highest Risk Ratio (RR): 1.05; 95% CI: 1.02-1.08), and were highest when wind events cooccurred with PO (highest RR: 1.14; 95% CI: 1.10-1.18), but not during PO alone (RR: 1.00; 95%CI: 0.96-1.04). The increase was also observed with all subgroups through Day 2 after the event. Greater risks exist for older adults (≥65 years) and those on Medicaid. After the joint occurrences of wind events and PO, average visits are 0.2 days longer, and cost 13% more, compared to no wind/no PO days., Conclusion: There is a significant increase in ED visits, length of stay and cost of injuries during wind events, especially when they coupled with PO and especially among older cases and Medicaid holders. Our findings may be used for planning disaster preparedness and recovery efforts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Youth of color from low-income urban communities are crucial participants in research, as their involvement can shape effective, culturally responsive interventions and policy to promote youth health and well-being. These young people, however, are an often-neglected research population, due in part to perceived challenges associated with their inclusion as well as marginalized communities' justifiable mistrust of research., Objectives: Based on our experience conducting a school-based randomized intervention trial in Baltimore, Maryland, we present strategies for conducting research with low-income, urban youth of color. We discuss strategies in three domains: university-community partnership development, participant recruitment, and participant retention., Methods: We reviewed partnership building and recruitment strategies employed by our team across four years of trial implementation and evaluated success of participant retention at our final survey timepoint., Results: Partnership building was facilitated by selection of a study design that maximized benefits for all participants, promotion of capacity building at partner institutions, and attention to research staff hiring and training practices. Effective study recruitment strategies included personal contact with parents and close cooperation between school personnel and study staff. Providing incentives and collecting multiple types of participant contact information contributed to increased retention rates. On average, those who participated in the final survey timepoint were less likely to be male and Latinx and exhibited more favorable baseline mental health than those who did not, suggesting differential attrition based on youth characteristics., Conclusions: Lessons learned from this school-based trial can be applied more broadly to research with low-income urban youth of color. Researchers should strive to maximize scientific rigor, minimize harm to vulnerable adolescents and their communities, promote positive research experiences for young people, and provide concrete benefits to those who participate., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Considering that several meteorological variables can contribute to weather vulnerability, the estimation of their synergetic effects on health is particularly useful. The spatial synoptic classification (SSC) has been used in biometeorological applications to estimate the effect of the entire suite of weather conditions on human morbidity and mortality. In this study, we assessed the relationships between extremely hot and dry (dry tropical plus, DT+) and hot and moist (moist tropical plus, MT+) weather types in summer and extremely cold and dry (dry polar plus, DP+) and cold and moist (moist polar, MP+) weather types in winter and cardiovascular and respiratory hospitalizations by age and sex. Time-series quasi-Poisson regression with distributed lags was used to assess the relationship between oppressive weather types and daily hospitalizations over 14 subsequent days in the extended summer (May to August) and 28 subsequent days during the extended winter (November to March) over 24 years in 4 Swedish locations from 1991 to 2014. In summer, exposure to hot weather types appeared to reduce cardiovascular hospitalizations while increased the risk of hospitalizations for respiratory diseases, mainly related to MT+. In winter, the effect of cold weather on both cause-specific hospitalizations was small; however, MP+ was related to a delayed increase in cardiovascular hospitalizations, whilst MP+ and DP + increased the risk of hospitalizations due to respiratory diseases. This study provides useful information for the staff of hospitals and elderly care centers who can help to implement protective measures for patients and residents. Also, our results could be helpful for vulnerable people who can adopt protective measures to reduce health risks., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: COPD is the third leading cause of death in the United States, with 16 million Americans currently experiencing difficulty with breathing. Power outages could be life-threatening for those relying on electricity. However, significant gaps remain in understanding the potential impact of power outages on COPD exacerbations., Research Question: The goal of this study was to determine how power outages affect COPD exacerbations., Study Design and Methods: Using distributed lag nonlinear models controlling for time-varying confounders, the hospitalization rate during a power outage was compared vs non-outage periods to determine the rate ratio (RR) for COPD and its subtypes at each of 0 to 6 lag days in New York State from 2001 to 2013. Stratified analyses were conducted according to sociodemographic characteristics, season, and clinical severity; changes were investigated in numerous critical medical indicators, including length of stay, hospital cost, the number of comorbidities, and therapeutic procedures between the two periods., Results: The RR of COPD hospitalization following power outages ranged from 1.03 to 1.39 across lag days. The risk was strongest at lag 0 and lag 1 days and lasted significantly for 7 days. Associations were stronger for the subgroup with acute bronchitis (RR, 1.08-1.69) than for cases of acute exacerbation (RR, 1.03-1.40). Compared with non-outage periods, the outage period was observed to be $4.67 thousand greater in hospital cost and 1.38 greater in the number of comorbidities per case. The average cost (or number of comorbidities) was elevated in all groups stratified according to cost (or number of comorbidities). In contrast, changes in the average length of stay (-0.43 day) and the average number of therapeutic procedures (-0.09) were subtle., Interpretation: Power outages were associated with a significantly elevated rate of COPD hospitalization, as well as greater costs and number of comorbidities. The average cost and number of comorbidities were elevated in all clinical severity groups., (Copyright © 2020 American College of Chest Physicians. All rights reserved.)

Many people around the world are impacted by some form of bodily pain. Outside factors, such as weather, are thought to help trigger pain, especially in those who have pain-related conditions. When it comes to human health and comfort, understanding the potential external factors that aide in triggering pain is essential. Identifying such factors makes prevention and treatment of pain more feasible. This study focused on how those who suffer from various pain-related conditions (fibromyalgia, rheumatoid arthritis, osteoarthritis, and general back pain) are impacted by different synoptic weather types (i.e., air masses). Synoptic weather types and emergency department (ED) visits for pain in select central North Carolina counties were collected over a seven-year period to determine a potential relationship. Bootstrapped confidence intervals revealed that moist tropical weather types resulted in the highest number of ED visits for each of the conditions examined, while moist polar weather types often resulted in the fewest. The barometric pressure changes associated with transitional weather types, which are often associated with fronts, did not have any significant relationships with pain.

The spatial synoptic classification (SSC) is a holistic categorical assessment of the daily weather conditions at specific locations; it is a useful tool for assessing weather effects on health. In this study, we assessed (a) the effect of hot weather types and the duration of heat events on cardiovascular and respiratory mortality in summer and (b) the effect of cold weather types and the duration of cold events on cardiovascular and respiratory mortality in winter. A time-stratified case-crossover design combined with a distributed lag nonlinear model was carried out to investigate the association of weather types with cause-specific mortality in two southern (Skåne and Stockholm) and two northern (Jämtland and Västerbotten) locations in Sweden. During summer, in the southern locations, the Moist Tropical (MT) and Dry Tropical (DT) weather types increased cardiovascular and respiratory mortality at shorter lags; both hot weather types substantially increased respiratory mortality mainly in Skåne. The impact of heat events on mortality by cardiovascular and respiratory diseases was more important in the southern than in the northern locations at lag 0. The cumulative effect of MT, DT and heat events lagged over 14 days was particularly high for respiratory mortality in all locations except in Jämtland, though these did not show a clear effect on cardiovascular mortality. During winter, the dry polar and moist polar weather types and cold events showed a negligible effect on cardiovascular and respiratory mortality. This study provides valuable information about the relationship between hot oppressive weather types with cause-specific mortality; however, the cold weather types may not capture sufficiently effects on cause-specific mortality in this sub-Arctic region.

Background: While previous studies uncovered individual vulnerabilities to health risks during catastrophic storms, few evaluated the population vulnerability which is more important for identifying areas in greatest need of intervention., Objectives: We assessed the association between community factors and multiple health outcomes, and developed a community vulnerability index., Methods: We retained emergency department visits for several health conditions from the 2005-2014 New York Statewide Planning and Research Cooperative System. We developed distributed lag nonlinear models at each spatial cluster across eight counties in downstate New York to evaluate the health risk associated with Superstorm Sandy (10/28/2012-11/9/2012) compared to the same period in other years, then defined census tracts in clusters with an elevated risk as "risk-elevated communities", and all others as "unelevated". We used machine-learning techniques to regress the risk elevation status against community factors to determine the contribution of each factor on population vulnerability, and developed a community vulnerability index (CVI)., Results: Overall, community factors had positive contributions to increased community vulnerabilities to Sandy-related substance abuse (91.35%), injuries (70.51%), cardiovascular diseases (8.01%), and mental disorders (2.71%) but reversely contributed to respiratory diseases (-34.73%). The contribution of low per capita income (max: 22.08%), the percentage of residents living in group quarters (max: 31.39%), the percentage of areas prone to flooding (max: 38.45%), and the percentage of green coverage (max: 29.73%) tended to be larger than other factors. The CVI based on these factors achieved an accuracy of 0.73-0.90 across outcomes., Conclusions: Our findings suggested that substance abuse was the most sensitive disease susceptible to less optimal community indicators, whereas respiratory diseases were higher in communities with better social environment. The percentage of residents in group quarters and areas prone to flooding were among dominant predictors for community vulnerabilities. The CVI based on these factors has an appropriate predictive performance., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Paramedics are among the most frequently injured health professionals in Australia. A lack of physical capacity may contribute to injury risk in this occupational population., Aims: This study sought to describe and compare the physical fitness of male and female paramedics across age groups to ascertain differences in physical capacity., Methods: A group of regional Australian paramedics (n = 140; 78 males; mean ± SD 37.4 ± 9.9 years; body mass index 28.1 ± 4.9 kg/m2) underwent a fitness assessment. Measures included upper, lower and core-body muscular strength and flexibility. Outcomes were compared between genders and across age groups using two-way between-groups analysis of variance., Results: Male paramedics had greater upper body strength (P < 0.05; push-ups) mean (95% CI): 22.6 (19.4-25.9) versus 18.7 (15.2-22.3); similar lower body strength (single-leg wall squat): 39.0 (32.6-45.3) s versus 36.7 (27.1-46.3) s; greater core strength (P < 0.05; prone plank hold): 87.9 (77.6-98.3) s versus 73.8 (63.7-83.8) s; similar upper body flexibility (back scratch): -4.0 (-6.7 to -1.3) cm versus -0.3 (-2.2 to 1.7) cm; and similar lower body flexibility (sit and reach): 20.4 (18.2-22.6) cm versus 26.1 (23.5-28.7) cm to female paramedics. Core, upper and lower body strength all decreased with age (P < 0.05)., Conclusions: Core, upper and lower body strength and upper body flexibility were poorer for older compared to younger regional paramedics in New South Wales, Australia. Future research should investigate whether these outcomes are associated with occupational injury risk. This information would assist in the design of injury prevention interventions for paramedics such as tailored workplace exercise programs., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Previous research reports associations between air pollution measured during pregnancy and the occurrence of congenital heart defects (CHDs) in offspring. The objective of this research was to assess if exposure to extreme heat events (EHEs) during pregnancy may modify this association., Methods: The study population consisted of 4,033 controls and 2,632 cases with dates of delivery between 1999 and 2007 who participated in the National Birth Defects Prevention Study, a multi-site case-control study in the United States. Daily data from the closest stationary fine particulate matter (PM 2.5 ) monitor within 50 km from the maternal residence were averaged across weeks 3-8 post-conception. EHEs were defined as maximum ambient temperature in the upper 95th percentile for at least 2 consecutive days or the upper 90th percentile for 3 consecutive days. Logistic regression models were adjusted for maternal age, ethnicity, education, and average humidity. Relative excess risks due to interaction (RERI) were calculated., Results: Compared with women with low PM 2.5 exposure and no exposure to an EHE, the odds of a ventricular septal defect in offspring associated with high PM 2.5 exposure was elevated only among women who experienced an EHE (odds ratio [OR] 2.14 95% confidence interval [CI] 1.19, 3.38 vs. OR 0.97 95% CI 0.49, 1.95; RERI 0.82 95% CI -0.39, 2.17). The majority of observed associations and interactions for other heart defects were null and/or inconclusive due to lack of precision., Conclusions: This study provides limited evidence that EHEs may modify the association between prenatal exposure to PM 2.5 and CHD occurrence., (Copyright © 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Environmental Epidemiology. All rights reserved.)

Introduction: Spending a few hours to cool down in a cooling center reduces the impact of heat on health. But limited or lack of accessibility of these facilities is often a barrier to their utilization. The objective of this study was to assess accessibility of the cooling centers to heat-vulnerable populations in New York State (NYS) by various modes of transportation., Methods: We estimate the proximity of 377 cooling centers to general and heat-vulnerable populations in NYS (excluding New York City (NYC)) and determine their accessibility via walking, public transportation and driving. Distances between tract populations and nearest cooling center, and between cooling centers and public transportation stops were estimated. Accessibility in four metropolitan regions was determined via public transportation while accessibility in heat-vulnerable rural areas was estimated via driving., Results: Distances to nearest cooling center ranged from 0 to 53.2 miles with only a third of NYS population within walking distance (0.5 miles) of a cooling center. About 51% of heat-vulnerable tracts were within 0.5 miles, with an average distance of 2.4 miles to the nearest cooling center. Within the four metro politan regions 80% of cooling centers within 0.5 miles of a public transportation stop. All cooling centers in heat-vulnerable tracts were accessible via public transportation. In rural heat-vulnerable tracts, driving distances averaged at about 18 miles., Conclusions: In urban areas many residents were not within walking distance of a cooling center, but most, and nearly all in the most heat-vulnerable areas, were within walking distance of public transportation to a cooling center. In rural locations distances were longer, and accessibility is a greater issue. Cooling centers can be a valuable resource for general and heat-vulnerable populations during an extreme heat event. When planning and implementing cooling centers, it is therefore important to improve accessibility and address other barriers that can hamper their utilization., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.

Much is known about the adverse health impact of high and low temperatures. The Spatial Synoptic Classification is a useful tool for assessing weather effects on health because it considers the combined effect of meteorological factors rather than temperature only. The aim of this study was to assess the association between oppressive weather types and daily total mortality in Sweden. Time-series Poisson regression with distributed lags was used to assess the relationship between oppressive weather (Dry Polar, Dry Tropical, Moist Polar, and Moist Tropical) and daily deaths over 14 days in the extended summer (May to September), and 28 days during the extended winter (November to March), from 1991 to 2014. Days not classified as oppressive weather served as the reference category. We computed relative risks with 95% confidence intervals, adjusting for trends and seasonality. Results of the southern (Skåne and Stockholm) and northern (Jämtland and Västerbotten) locations were pooled using meta-analysis for regional-level estimates. Analyses were performed using the dlnm and mvmeta packages in R. During summer, in the South, the Moist Tropical and Dry Tropical weather types increased the mortality at lag 0 through lag 3 and lag 6, respectively. Moist Polar weather was associated with mortality at longer lags. In the North, Dry Tropical weather increased the mortality at shorter lags. During winter, in the South, Dry Polar and Moist Polar weather increased mortality from lag 6 to lag 10 and from lag 19 to lag 26, respectively. No effect of oppressive weather was found in the North. The effect of oppressive weather types in Sweden varies across seasons and regions. In the North, a small study sample reduces precision of estimates, while in the South, the effect of oppressive weather types is more evident in both seasons., Competing Interests: The authors declare no conflict of interest.

While the impact of absolute extreme temperatures on human health has been amply studied, far less attention has been given to relative temperature extremes, that is, events that are highly unusual for the time of year but not necessarily extreme relative to a location's overall climate. In this research, we use a recently defined extreme temperature event metric to define absolute extreme heat events (EHE) and extreme cold events (ECE) using absolute thresholds, and relative extreme heat events (REHE) and relative extreme cold events (RECE) using relative thresholds. All-cause mortality outcomes using a distributed lag nonlinear model are evaluated for the largest 51 metropolitan areas in the US for the period 1975-2010. Both the immediate impacts and the cumulative 20-day impacts are assessed for each of the extreme temperature event types. The 51 metropolitan areas were then grouped into 8 regions for meta-analysis. For heat events, the greatest mortality increases occur with a 0-day lag, with the subsequent days showing below-expected mortality (harvesting) that decreases the overall cumulative impact. For EHE, increases in mortality are still statistically significant when examined over 20 days. For REHE, it appears as though the day-0 increase in mortality is short-term displacement. For cold events, both relative and absolute, there is little mortality increase on day 0, but the impacts increase on subsequent days. Cumulative impacts are statistically significant at more than half of the stations for both ECE and RECE. The response to absolute ECE is strongest, but is also significant when using RECE across several southern locations, suggesting that there may be a lack of acclimatization, increasing mortality in relative cold events both early and late in winter.

Background More intense and longer-lasting heat events are expected in the United States as a consequence of climate change. This study aimed to project the potential changes in maternal heat exposure during early pregnancy (3-8 weeks post conception) and the associated burden of congenital heart defects ( CHD s) in the future. Methods and Results This study expanded on a prior nationwide case-control study that evaluated the association between CHD s and maternal heat exposure during early pregnancy in summer and spring. We defined multiple indicators of heat exposure, and applied published odds ratios obtained for the matching season of the baseline (1995-2005) into the projection period (2025-2035) to estimate potential changes in CHD burden throughout the United States. Increases in maternal heat exposure were projected across the United States and to be larger in the summer. The Midwest will potentially have the highest increase in summer maternal exposure to excessively hot days (3.42; 95% CI, 2.99-3.88 per pregnancy), heat event frequency (0.52; 95% CI, 0.44-0.60) and heat event duration (1.73; 95% CI, 1.49-1.97). We also found large increases in specific CHD subtypes during spring, including a 34.0% (95% CI, 4.9%-70.8%) increase in conotruncal CHD in the South and a 38.6% (95% CI , 9.9%-75.1%) increase in atrial septal defect in the Northeast. Conclusions Projected increases in maternal heat exposure could result in an increased CHD burden in certain seasons and regions of the United States.

Many studies have analyzed the effects of extreme heat on human mortality, however fewer studies have focused on the effects of cold related mortality due to the complicated nature of the lagged response. This study utilized a Distributed Lag Non-Linear Model with a 30-day lag to determine the cumulative effects of extreme cold events (ECEs) on mortality across 32 cities in the United States for the period of 1975-2010. ECEs were divided into specific categories based on duration, magnitude, and timing of occurrence. Mortality was divided into all-age mortality as well as mortality of individuals >64 years old. The findings suggest a strong relationship between a city's latitude as well as the timing of an ECE with mortality. Early season ECEs result in a much higher relative risk of increased mortality, particularly in cities with higher mean winter temperatures, while the RR of mortality of individuals >64 was consistently higher for each city. This study suggests early season ECEs should receive enhanced preparedness efforts as individuals may be particularly vulnerable when not acclimatized to extreme cold., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Limited epidemiologic research exists on the association between weather-related extreme heat events (EHEs) and orofacial clefts (OFCs). We estimated the associations between maternal exposure to EHEs in the summer season and OFCs in offspring and investigated the potential modifying effect of body mass index on these associations., Methods: We conducted a population-based case-control study among mothers who participated in the National Birth Defects Prevention Study for whom at least 1 day of their first two post-conception months occurred during summer. Cases were live-born infants, stillbirths, and induced terminations with OFCs; controls were live-born infants without major birth defects. We defined EHEs using the 95th and the 90th percentiles of the daily maximum universal apparent temperature distribution. We used unconditional logistic regression with Firth's penalized likelihood method to estimate adjusted odds ratios and 95% confidence intervals, controlling for maternal sociodemographic and anthropometric variables., Results: We observed no association between maternal exposure to EHEs and OFCs overall, although prolonged duration of EHEs may increase the risk of OFCs in some study sites located in the Southeast climate region. Analyses by subtypes of OFCs revealed no associations with EHEs. Modifying effect by BMI was not observed., Conclusions: We did not find a significantly increased risk of OFCs associated with maternal exposure to EHEs during the relevant window of embryogenesis. Future studies should account for maternal indoor and outdoor activities and for characteristics such as hydration and use of air conditioning that could modify the effect of EHEs on pregnant women., (© 2018 Wiley Periodicals, Inc.)

Objectives: The frequency and intensity of extreme heat events are increasing in New York State (NYS) and have been linked with increased heat-related morbidity and mortality. But these effects are not uniform across the state and can vary across large regions due to regional sociodemographic and environmental factors which impact an individual's response or adaptive capacity to heat and in turn contribute to vulnerability among certain populations. We developed a heat vulnerability index (HVI) to identify heat-vulnerable populations and regions in NYS., Study Design: Census tract level environmental and sociodemographic heat-vulnerability variables were used to develop the HVI to identify heat-vulnerable populations and areas., Methods: Variables were identified from a comprehensive literature review and climate-health research in NYS. We obtained data from 2010 US Census Bureau and 2011 National Land Cover Database. We used principal component analysis to reduce correlated variables to fewer uncorrelated components, and then calculated the cumulative HVI for each census tract by summing up the scores across the components. The HVI was then mapped across NYS (excluding New York City) to display spatial vulnerability. The prevalence rates of heat stress were compared across HVI score categories., Results: Thirteen variables were reduced to four meaningful components representing 1) social/language vulnerability; 2) socioeconomic vulnerability; 3) environmental/urban vulnerability; and 4) elderly/ social isolation. Vulnerability to heat varied spatially in NYS with the HVI showing that metropolitan areas were most vulnerable, with language barriers and socioeconomic disadvantage contributing to the most vulnerability. Reliability of the HVI was supported by preliminary results where higher rates of heat stress were collocated in the regions with the highest HVI., Conclusions: The NYS HVI showed spatial variability in heat vulnerability across the state. Mapping the HVI allows quick identification of regions in NYS that could benefit from targeted interventions. The HVI will be used as a planning tool to help allocate appropriate adaptation measures like cooling centers and issue heat alerts to mitigate effects of heat in vulnerable areas., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Temperature-mortality relationships are nonlinear, time-lagged, and can vary depending on the time of year and geographic location, all of which limits the applicability of simple regression models in describing these associations. This research demonstrates the utility of an alternative method for modeling such complex relationships that has gained recent traction in other environmental fields: nonlinear autoregressive models with exogenous input (NARX models). All-cause mortality data and multiple temperature-based data sets were gathered from 41 different US cities, for the period 1975-2010, and subjected to ensemble NARX modeling. Models generally performed better in larger cities and during the winter season. Across the US, median absolute percentage errors were 10% (ranging from 4% to 15% in various cities), the average improvement in the r-squared over that of a simple persistence model was 17% (6-24%), and the hit rate for modeling spike days in mortality (>80th percentile) was 54% (34-71%). Mortality responded acutely to hot summer days, peaking at 0-2 days of lag before dropping precipitously, and there was an extended mortality response to cold winter days, peaking at 2-4 days of lag and dropping slowly and continuing for multiple weeks. Spring and autumn showed both of the aforementioned temperature-mortality relationships, but generally to a lesser magnitude than what was seen in summer or winter. When compared to distributed lag nonlinear models, NARX model output was nearly identical. These results highlight the applicability of NARX models for use in modeling complex and time-dependent relationships for various applications in epidemiology and environmental sciences., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The aims of this study are to explore the "offensive" summer weather types classified under the spatial synoptic classification (SSC) system and to evaluate their impacts on excess mortality in 14 Korean cities. All-cause deaths per day for the entire population were examined over the summer months (May-September) of 1991-2010. Daily deaths were standardized to account for long-term trends of subcycles (annual, seasonal, and weekly) at the mid-latitudes. In addition, a mortality prediction model was constructed through multiple stepwise regression to develop a heat-health warning system based on synoptic climatology. The result showed that dry tropical (DT) days during early summer caused excess mortality due to non-acclimatization by inhabitants, and moist tropical (MT) plus and double plus resulted in greater spikes of excess mortality due to extremely hot and humid conditions. Among the 14 Korean cities, highly excess mortality for the elderly was observed in Incheon (23.2%, 95%CI 5.6), Seoul (15.8%, 95%CI 2.6), and Jeonju (15.8%, 95%CI 4.6). No time lag effect was observed, and excess mortality gradually increased with time and hot weather simultaneously. The model showed weak performance as its predictions were underestimated for the validation period (2011-2015). Nevertheless, the results clearly revealed the efficiency of relative and multiple-variable approaches better than absolute and single-variable approaches. The results indicate the potential of the SSC as a suitable system for investigating heat vulnerability in South Korea, where hot summers could be a significant risk factor.

This study investigates the relationship between all-cause mortality and extreme temperature events (ETEs) from 1975 to 2004. For 50 U.S. locations, these heat and cold events were defined based on location-specific thresholds of daily mean apparent temperature. Heat days were defined by a 3-day mean apparent temperature greater than the 95th percentile while extreme heat days were greater than the 97.5th percentile. Similarly, calculations for cold and extreme cold days relied upon the 5th and 2.5th percentiles. A distributed lag non-linear model assessed the relationship between mortality and ETEs for a cumulative 14-day period following exposure. Subsets for season and duration effect denote the differences between early- and late-season as well as short and long ETEs. While longer-lasting heat days resulted in elevated mortality, early season events also impacted mortality outcomes. Over the course of the summer season, heat-related risk decreased, though prolonged heat days still had a greater influence on mortality. Unlike heat, cold-related risk was greatest in more southerly locations. Risk was highest for early season cold events and decreased over the course of the winter season. Statistically, short episodes of cold showed the highest relative risk, suggesting unsettled weather conditions may have some relationship to cold-related mortality. For both heat and cold, results indicate higher risk to the more extreme thresholds. Risk values provide further insight into the role of adaptation, geographical variability, and acclimatization with respect to ETEs.

Background: Elevated body core temperature has been shown to have teratogenic effects in animal studies. Our study evaluated the association between weather-related extreme heat events (EHEs) in the summer season and neural tube defects (NTDs), and further investigated whether pregnant women with a high pregestational body mass index (BMI) have a greater risk of having a child with NTDs associated with exposure to EHE than women with a normal BMI., Methods: We conducted a population-based case-control study among mothers of infants with NTDs and mothers of infants without major birth defects, who participated in the National Birth Defects Prevention Study and had at least 1 day of the third or fourth week postconception during summer months. EHEs were defined using the 95 th and the 90 th percentiles of the daily maximum universal apparent temperature. Adjusted odds ratios and 95% confidence intervals were calculated using unconditional logistic regression models with Firth's penalized likelihood method while controlling for other known risk factors., Results: Overall, we did not observe a significant association between EHEs and NTDs. At the climate region level, consistently elevated but not statistically significant estimates were observed for at least 2 consecutive days with daily universal apparent maximum temperature above the 95 th percentile of the UATmax distribution for the season, year, and weather monitoring station in New York (Northeast), North Carolina and Georgia (Southeast), and Iowa (Upper Midwest). No effect modification by BMI was observed., Conclusion: EHEs occurring during the relevant developmental window of embryogenesis do not appear to appreciably affect the risk of NTDs. Future studies should refine exposure assessment, and more completely account for maternal activities that may modify the effects of weather exposure. Birth Defects Research 109:1482-1493, 2017.© 2017 Wiley Periodicals, Inc., (© 2017 Wiley Periodicals, Inc.)

The International Journal of Biometeorology (IJB) has continuously evolved since its first publications in 1957. In this paper, we examine these changes using a database that includes all manuscript titles and author information. A brief history considers the development of the journal and shifts over time. With an interdisciplinary focus, publications draw on a wide array of subdisciplines. Using content analysis, we evaluate the themes found within IJB. Some research themes have maintained prominence throughout the journal's history, while other themes have waxed or waned over time. Similarly, the most influential manuscripts throughout the past 60 years reveal that human biometeorological papers, particularly regarding thermal comfort, have been influential throughout the journal's history, with other themes, including phenology and animal biometeorology, more concentrated in specific periods. Dominated by North America and Europe in the early years, publication authorship has shifted over the last decade to be more globally representative. Recent inclusion of special issues devoted to regional biometeorological issues, as well as to Students and New Professionals, offer insight into the future direction of the IJB.

Local agencies in New York State (NYS) set up cooling centers to provide relief from summer-time heat especially for people with limited access to air-conditioning. We aimed to determine cooling center locations in NYS, and explore county agencies' involvement in organizing and promoting utilization of cooling centers. We conducted a survey among county health and emergency preparedness offices in NYS (excluding NYC) and explored official county websites. We identified 377 cooling centers, mostly in metropolitan areas of NYS. Although 47 % of counties listed locations online, only 29 % reported locations via survey. Radio (90 %) and internet (84 %) were popular for information dissemination. Air-conditioning was available at all indoor cooling center facilities. Cooling centers in 13 % of the counties were accessible by either public transportation or shuttles arranged by the facility. About 38 % counties do not consider cooling centers important in their region or promote informal cooling centers. More than a third of New York counties had neither cooling centers nor plans to establish a cooling center as extreme heat was not perceived as a threat in their region.

Aims: Hypothermia is a medical condition characterized by a drop in core body temperature, and it is a considerable source of winter weather-related vulnerability in mid-/high-latitude areas. Heat vulnerability research, including assessments of internet-based resources, is more thoroughly represented in the peer-reviewed literature than cold-related vulnerability research. This study was undertaken to summarize available web-based hypothermia information, and then determine its scientific validity compared to the peer-reviewed literature., Methods: This research takes a similar approach used by Hajat et al. for web-based heat vulnerability research, and utilizes this framework to assess hypothermia information found on the internet. Hypothermia-related search terms were used to obtain websites containing hypothermia information, and PubMed (medical literature search engine) and Google Scholar were used to identify peer-reviewed hypothermia literature. The internet information was aggregated into categories (vulnerable populations, symptoms, prevention), which were then compared to the hypothermia literature to determine the scientific validity of the web-based guidance. The internet information was assigned a Strength of Recommendation Taxonomy (SORT) grade (developed by the American Academy of Family Practitioners) of A, B, or C based on the peer-reviewed evidence., Results: Overall, 25 different pieces of guidance within the three categories were identified on 49 websites. Guidance concerning hypothermia symptoms most frequently appeared on websites, with six symptoms appearing on 50% or greater of websites. No piece of guidance within the vulnerable population categories appeared on greater than 60% of the websites, and prevention-related guidance was characterized by varied SORT grades., Conclusions: Hypothermia information on the internet was not entirely congruent with the information within the peer-reviewed medical literature. Several suggestions for improving web-based hypothermia resources include clearly listing sources for users to see and eliminating guidance with lower SORT grades and replacing with evidence-based information., (© Royal Society for Public Health 2014.)

While the impacts of heat upon mortality and morbidity have been frequently studied, few studies have examined the relationship between heat, morbidity, and mortality across the same events. This research assesses the relationship between heat events and morbidity and mortality in New York City for the period 1991-2004. Heat events are defined based on oppressive weather types as determined by the Spatial Synoptic Classification. Morbidity data include hospitalizations for heat-related, respiratory, and cardiovascular causes; mortality data include these subsets as well as all-cause totals. Distributed-lag models assess the relationship between heat and health outcome for a cumulative 15-day period following exposure. To further refine analysis, subset analyses assess the differences between early- and late-season events, shorter and longer events, and earlier and later years. The strongest heat-health relationships occur with all-cause mortality, cardiovascular mortality, and heat-related hospital admissions. The impacts of heat are greater during longer heat events and during the middle of summer, when increased mortality is still statistically significant after accounting for mortality displacement. Early-season heat waves have increases in mortality that appear to be largely short-term displacement. The impacts of heat on mortality have decreased over time. Heat-related hospital admissions have increased during this time, especially during the earlier days of heat events. Given the trends observed, it suggests that a greater awareness of heat hazards may have led to increased short-term hospitalizations with a commensurate decrease in mortality.

Annual suicide deaths outnumber the total deaths from homicide and war combined. Suicide is a complex behavioral endpoint, and a simple cause-and-effect model seems highly unlikely, but relationships with weather could yield important insight into the biopsychosocial mechanisms involved in suicide deaths. This study has been designed to test for a relationship between air temperature and suicide frequency that is consistent enough to offer some predictive abilities. Weekly suicide death totals and anomalies from Toronto, Ontario, Canada (1986-2009) and Jackson, Mississippi, USA (1980-2006) are analyzed for relationships by using temperature anomaly data and a distributed lag nonlinear model. For both analysis methods, anomalously cool weeks show low probabilities of experiencing high-end suicide totals while warmer weeks are more likely to experience high-end suicide totals. This result is consistent for Toronto and Jackson. Weekly suicide totals demonstrate a sufficient association with temperature anomalies to allow some prediction of weeks with or without increased suicide frequency. While this finding alone is unlikely to have immediate clinical implications, these results are an important step toward clarifying the biopsychosocial mechanisms of suicidal behavior through a more nuanced understanding of the relationship between temperature and suicide.

While the relationship between weather and human health has been studied from various perspectives, this study examines an alternative method of analysis by examining weather conditions on specific high-mortality days during the winter season. These high-mortality days, by definition, represent days with dramatic increases in mortality and the days with the highest mortality. By focusing solely on high-mortality days, this research examines the relationship between weather variables and mortality through a synoptic climatology, environment-to circulation approach. The atmospheric conditions during high-mortality days were compared to the days prior and the days not classified as high-mortality days. Similar patterns emerged across all five locations despite the spatial and temporal variability. Southern locations had a stronger relationship with temperature changes while northern locations showed a greater relationship to atmospheric pressure. Overall, all high-mortality days were associated with warmer temperatures, decreased pressure, and a greater likelihood of precipitation when compared to the previous subset of days. While the atmospheric conditions were consistent across all locations, the importance of the lag effect should not be overlooked as a contributing factor to mortality during the winter season. Through a variety of diverse, methodological approaches, future studies may build upon these results and explore in more detail the complex relationship between weather situations and the impact of short-term changes in weather and health outcomes.

Many previous studies have looked into the relationship between asthma and individual weather variables, but comparatively few have looked at this relationship using holistic weather types (WTs). Utilizing the Spatial Synoptic Classification, this research considers up to 6 days of lag time while investigating the asthma-to-WT relationship in two age groups (under 18 and 18 and over) throughout New York State. Results indicate that a cold and dry WT in autumn corresponds to increased asthma admissions and spike days in admissions in New York City (NYC) for the school-aged population, while hot and dry WTs in summer correspond to spike days in asthma admissions in both age groups. However, results vary considerably for other regions, seasons and WTs, and spike day analysis yields clearer results than the analysis of total anomalous admissions. When stratified by multiple regions and age groups, the sample size of daily asthma admissions is a limiting factor outside of NYC.

Objectives: We compared the ability of several heat-health warning systems to predict days of heat-associated mortality using common data sets., Methods: Heat-health warning systems initiate emergency public health interventions once forecasts have identified weather conditions to breach predetermined trigger levels. We examined 4 commonly used trigger-setting approaches: (1) synoptic classification, (2) epidemiologic assessment of the temperature-mortality relationship, (3) temperature-humidity index, and (4) physiologic classification. We applied each approach in Chicago, Illinois; London, United Kingdom; Madrid, Spain; and Montreal, Canada, to identify days expected to be associated with the highest heat-related mortality., Results: We found little agreement across the approaches in which days were identified as most dangerous. In general, days identified by temperature-mortality assessment were associated with the highest excess mortality., Conclusions: Triggering of alert days and ultimately the initiation of emergency responses by a heat-health warning system varies significantly across approaches adopted to establish triggers.

To examine the efficacy of municipal heat watch warning systems, a thorough evaluation of the heat mitigation plans of four North American cities--Dayton (Ohio, USA), Philadelphia (Pennsylvania, USA), Phoenix (Arizona, USA), and Toronto (Ontario, Canada)--was undertaken. In concert with this evaluation was a survey of residents in the metropolitan areas of these cities that gauged their perception of their own vulnerability to the heat, as well as their knowledge of heat warnings and the activities recommended to be undertaken to help mitigate the effects of the heat. In total, 908 respondents participated in the telephone survey. Some of the key results indicate that knowledge of the heat warning was nearly universal (90%), and likely due to pervasive media coverage more than any other means. Though knowledge of the event was widespread, knowledge of what to do was less common. Only around half of all respondents mentioned that they changed their behavior, and despite the diversity of information available on mitigating heat vulnerability, most respondents stated that they merely "avoided the outdoors" at all costs. Though air conditioning was nearly ubiquitous among respondents, over a third mentioned that economic factors of energy costs were considered in terms of how long or whether the air conditioner was turned on.

Heat is the leading weather-related killer in the United States. Although previous research suggests that social influences affect human responses to natural disaster warnings, no studies have examined the social impacts of heat or heat warnings on a population. Here, 201 surveys were distributed in Metropolitan Phoenix to determine the social impacts of the heat warning system, or more specifically, to gauge risk perception and warning response. Consistent with previous research, increased risk perception of heat results in increased response to a warning. Different social factors such as sex, race, age, and income all play an important role in determining whether or not people will respond to a warning. In particular, there is a strong sense of perceived risk to the heat among Hispanics which translates to increased response when heat warnings are issued. Based on these findings, suggestions are presented to help improve the Phoenix Heat Warning System.

This study investigates the relationship between tree growth and air mass type variability, using the spatial synoptic classification (SSC) in a bottomland slash pine forest in coastal Alabama (USA). The use of an air mass approach in dendroclimatology is somewhat unconventional and has not been fully explored. However, we believe that it may be useful because the air mass approach represents a holistic and comprehensive measure of surface conditions. Cores from 36 slash pines (Pinus elliotti) were extracted and ring widths were measured to the nearest 0.01 mm. The cores were then cross-dated and a standardized ring index series was established. Relationships were explored between the index series and several climate variables and teleconnections. The index series showed significant relationships with SSC air mass types and SSC air mass ratios, but insignificant results with teleconnections. Specifically the Dry Tropical air mass type was negatively correlated with tree growth while Moist Moderate was positively correlated. Concomitantly, Dry Tropical : Moist Moderate, Dry Tropical : Moist Tropical, and Dry Moderate : Moist Moderate air mass ratios also showed negative correlations. Positive Pacific Decadal Oscillation (PDO) sea surface temperatures were also associated with significant moisture and air mass variability in the region, although the PDO did not have a significant relationship with tree growth. The significance between SSC air mass variability and tree growth in the humid subtropical climate of coastal Alabama has favorable implications for dendroclimatological research in drier environments where trees are more sensitive to climatic variables.

Concern over the impact of extreme heat upon human health has increased in recent years. Though much research has evaluated the relationships between the two, few studies have attempted to quantify this vulnerability on a sub-metropolitan area level. Using a Geographic Information System (GIS), ambulance calls for a 4-year period from 1999 to 2002 was analyzed in relation to extreme heat for the city of Toronto, Ontario, Canada. Ambulance response calls were plotted on a map to understand the spatial variability of where calls significantly increase above normal levels during oppressively hot days. Census data were used to identify the demographic characteristics of the population within these areas. Statistical tests were also used to assess the degree of correlation among different meteorological variables and the ambulance call data. Over the 4-year period, the average number of ambulance calls increases by 10 percent over normal levels on those days considered oppressively hot. A change in the spatial pattern of calls also occurs on such days. The urban core, with the greatest density of calls, experiences the greatest absolute percentage increase in calls from normal on oppressive days. However, it is some areas of the city located along the shore of Lake Ontario, where a high majority of the population goes to cool down, that demonstrate the greatest percentage increase in calls. Other areas of the city exhibiting an increase in calls are located within industrial and recreational areas.

To assess whether meteorological conditions modify the relationship between short-term exposure to ambient air pollution and mortality, an examination of air pollution and human mortality associations (ecologic) using hybrid spatial synoptic classification procedures was conducted. Concentrations of air pollutants and human mortality from all non-accidental and cardiorespiratory causes were examined according to typical winter and summer synoptic climatologies in Toronto, Canada, between 1981 and 1999. Air masses were derived using a hybrid spatial synoptic classification procedure associating each day over the 19-year period with one of six different typical weather types, or a transition between two weather types. Generalized linear models (GLMs) were used to assess the risk of mortality from air pollution within specific air mass type subsets. Mortality follows a distinct seasonal pattern with a maximum in winter and a minimum in summer. Average air pollution concentrations were similar in both seasons with the exception of elevated sulfur dioxide levels in winter and elevated ozone levels in summer. Subtle changes in meteorological composition can alter the strength of pollutant associations with health outcomes, especially in the summer season. Although there does not appear to be any systematic patterning of modification, variation in pollutant concentrations seems dependent on the type of synoptic category present.

The magnitude of future climate change depends substantially on the greenhouse gas emission pathways we choose. Here we explore the implications of the highest and lowest Intergovernmental Panel on Climate Change emissions pathways for climate change and associated impacts in California. Based on climate projections from two state-of-the-art climate models with low and medium sensitivity (Parallel Climate Model and Hadley Centre Climate Model, version 3, respectively), we find that annual temperature increases nearly double from the lower B1 to the higher A1fi emissions scenario before 2100. Three of four simulations also show greater increases in summer temperatures as compared with winter. Extreme heat and the associated impacts on a range of temperature-sensitive sectors are substantially greater under the higher emissions scenario, with some interscenario differences apparent before midcentury. By the end of the century under the B1 scenario, heatwaves and extreme heat in Los Angeles quadruple in frequency while heat-related mortality increases two to three times; alpine/subalpine forests are reduced by 50-75%; and Sierra snowpack is reduced 30-70%. Under A1fi, heatwaves in Los Angeles are six to eight times more frequent, with heat-related excess mortality increasing five to seven times; alpine/subalpine forests are reduced by 75-90%; and snowpack declines 73-90%, with cascading impacts on runoff and streamflow that, combined with projected modest declines in winter precipitation, could fundamentally disrupt California's water rights system. Although interscenario differences in climate impacts and costs of adaptation emerge mainly in the second half of the century, they are strongly dependent on emissions from preceding decades.

Background: Seasonal variation has been demonstrated in many diseases, including certain skin diseases., Objective: To determine whether there is seasonal variation in dermatologic office visits in the USA., Methods: Data on dermatologic office visits were obtained from representative visits to outpatient physicians in the USA from the National Ambulatory Medical Care Survey from 1990 to 1998. Office visit seasonality was examined for all skin conditions, and individually for the 15 most commonly diagnosed conditions., Results: Office visits for skin conditions were seasonal (P = 0.002). The magnitude of variation can be roughly expressed by the following scheme: actinic keratosis (P = 0.0001) > acne (P = 0.0001) > folliculitis (P = 0.002) > dyschromia (P = 0.01) > seborrheic keratosis (P = 0.04) > psoriasis (P = 0.07) > seborrheic dermatitis (P = 0.09). Visits for skin cancer, not otherwise specified (skin cancer NOS), atopic dermatitis, cysts, common wart, wart, not otherwise specified (wart NOS), rosacea, contact dermatitis, and benign tumors showed no significant seasonal variations or trends., Conclusions: Dermatologic office visits are seasonal, with visits for individual diseases varying in their magnitude of seasonality. This seasonal variation may be a result of biological and nonbiological variables.