Perceptions of weather-based pain forecasts and their effect on daily activities.

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.

Projection of extreme heat- and cold-related mortality in Sweden based on the spatial synoptic classification.

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.

Mortality risk attributable to high and low ambient temperature in Pune city, India: A time series analysis from 2004 to 2012.

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.

Geographical variability in the relationship between synoptic weather type and emergency department visits for pain across North Carolina.

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.

Modeling complex effects of exposure to particulate matter and extreme heat during pregnancy on congenital heart defects: A U.S. population-based case-control study in the National Birth Defects Prevention Study.

BACKGROUND/OBJECTIVE: Research suggests gestational exposure to particulate matter ≤2.5 µm (PM2.5) and extreme heat may independently increase risk of birth defects. We investigated whether duration of gestational extreme heat exposure modifies associations between PM2.5 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 PM2.5 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 PM2.5 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/m3 increase in average PM2.5 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 PM2.5-septal defects relationship. Future research with enhanced exposure assessment and modeling techniques could clarify these relationships.

How neighborhood environment modified the effects of power outages on multiple health outcomes in New York state?

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.

The individual and synergistic impacts of windstorms and power outages on injury ED visits in New York State.

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.

Effect of extreme hot and cold weather on cause-specific hospitalizations in Sweden: A time series analysis.

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.

Relationship between synoptic weather type and emergency department visits for different types of pain across the Triangle region of North Carolina.

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.

Power Outage: An Ignored Risk Factor for COPD Exacerbations.

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 lag0 and lag1 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.

Hot and cold weather based on the spatial synoptic classification and cause-specific mortality in Sweden: a time-stratified case-crossover study.

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.

How community vulnerability factors jointly affect multiple health outcomes after catastrophic storms.

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.

Association between Weather Types based on the Spatial Synoptic Classification and All-Cause Mortality in Sweden, 1991⁻2014.

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.

The Mortality Response to Absolute and Relative Temperature Extremes.

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.

Projected Changes in Maternal Heat Exposure During Early Pregnancy and the Associated Congenital Heart Defect Burden in the United States.

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.

The influence of extreme cold events on mortality in 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.

Associations between fine particulate matter, extreme heat events, and congenital heart defects.

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 (PM2.5) 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 PM2.5 exposure and no exposure to an EHE, the odds of a ventricular septal defect in offspring associated with high PM2.5 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 PM2.5 and CHD occurrence.

A population-based case-control study of the association between weather-related extreme heat events and orofacial clefts.

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.

A new approach to modeling temperature-related mortality: Non-linear autoregressive models with exogenous input.

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.