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.

Increasing tree cover and high-albedo surfaces reduces heat-related ER visits in Los Angeles, CA.

There is an urgent need for strategies to reduce the negative impacts of a warming climate on human health. Cooling urban neighborhoods by planting trees and vegetation and increasing albedo of roofs, pavements, and walls can mitigate urban heat. We used synoptic climatology to examine how different tree cover and albedo scenarios would affect heat-related morbidity in Los Angeles, CA, USA, as measured by emergency room (ER) visits. We classified daily meteorological data for historical summer heat events into discrete air mass types. We analyzed those classifications against historical ER visit data to determine both heat-related and excess morbidity. We used the Weather Research and Forecasting model to examine the impacts of varied tree cover and albedo scenarios on meteorological outcomes and used these results with standardized morbidity data algorithms to estimate potential reductions in ER visits. We tested three urban modification scenarios of low, medium, and high increases of tree cover and albedo and compared these against baseline conditions. We found that avoiding 25% to 50% of ER visits during heat events would be a common outcome if the urban environment had more tree cover and higher albedo, with the greatest benefits occurring under heat events that are moderate and those that are particularly hot and dry. We conducted these analyses at the county level and compared results to a heat-vulnerable, working-class Los Angeles community with a high concentration of people of color, and found that reductions in the rate of ER visits would be even greater at the community level compared to the county.

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.

Interaction of maternal medication use with ambient heat exposure on congenital heart defects in the National Birth Defects Prevention Study.

BACKGROUND: Maternal exposure to weather-related extreme heat events (EHEs) has been associated with congenital heart defects (CHDs) in offspring. Certain medications may affect an individual's physiologic responses to EHEs. We evaluated whether thermoregulation-related medications modified associations between maternal EHE exposure and CHDs. METHODS: We linked geocoded residence data from the U.S. National Birth Defects Prevention Study, a population-based case-control study, to summertime EHE exposures. An EHE was defined using the 90th percentile of daily maximum temperature (EHE90) for each of six climate regions during postconceptional weeks 3-8. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between EHE90 and the risk of CHDs were estimated by strata of maternal thermoregulation-related medication use and climate region. Interaction effects were evaluated on multiplicative and additive scales. RESULTS: Over 45% of participants reported thermoregulation-related medication use during the critical period of cardiogenesis. Overall, these medications did not significantly modify the association between EHEs and CHDs. Still, medications that alter central thermoregulation increased aORs (95% CI) of EHE90 from 0.73 (0.41, 1.30) among non-users to 5.09 (1.20, 21.67) among users in the Southwest region, U.S. This effect modification was statistically significant on the multiplicative (P = 0.03) and additive scales, with an interaction contrast ratio (95% CI) of 1.64 (0.26, 3.02). CONCLUSION: No significant interaction was found for the maternal use of thermoregulation-related medications with EHEs on CHDs in general, while medications altering central thermoregulation significantly modified the association between EHEs and CHDs in Southwest U.S. This finding deserves further research.

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.

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.

The immediate effects of winter storms and power outages on multiple health outcomes and the time windows of vulnerability.

BACKGROUND: While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost. METHODS: We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM2.5. The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods. RESULTS: We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO. CONCLUSION: Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.

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.

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.

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.

Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model.

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.

Effects of heat waves on daily excess mortality in 14 Korean cities during the past 20 years (1991-2010): an application of the spatial synoptic classification approach.

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.

Differentiation of bony and soft-tissue adaptations of the shoulder in professional baseball pitchers.

BACKGROUND: Baseball pitching places tremendous forces on the arm, which may lead to structural tissue adaptations that are represented by changes in rotational range of motion (ROM). These adaptations often include both bony and soft tissue; however, the contribution of each tissue to the change in motion is not always clinically attainable. The purposes of this study were to determine the adaptations of ROM, bone, and soft tissue bilaterally and to examine the correlation between clinical ROM and humeral retroversion (HR)-corrected ROM. We hypothesized that glenohumeral internal rotation (IR) and total motion would be decreased and glenohumeral external rotation (ER), posterior capsule thickness (PCT), and HR would be increased in the dominant arm; that HR-corrected ROM would be significantly different than clinical ROM; and that HR-corrected ROM would be correlated with total motion difference. METHODS: Thirty professional baseball pitchers participated in this study. HR, PCT, and glenohumeral IR and ER were evaluated in the dominant and nondominant shoulders of each subject. RESULTS: The dominant arm exhibited significantly more retroversion, ER, and PCT than the nondominant arm. The dominant arm also had significantly less IR and total motion than the nondominant arm. The total ROM difference was significantly correlated with both HR-corrected glenohumeral IR deficit and ER gain. CONCLUSION: HR-corrected glenohumeral IR deficit and ER gain may more accurately reflect the contribution of soft-tissue changes to ROM. Unfortunately, measurement of HR is not always clinically attainable, making clinical management difficult.

Surveying Local Health Departments and County Emergency Management Offices on Cooling Centers as a Heat Adaptation Resource in New York State.

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.

Sixty years of the International Journal of Biometeorology.

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.

High-mortality days during the winter season: comparing meteorological conditions across 5 US cities.

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.

Ambient heat and diabetes hospitalizations: Does the timing of heat exposure matter?

BACKGROUND: Although ambient heat exposure is linked with diabetes mortality, the impacts of heat exposure on diabetes-related hospitalizations remain controversial. Previous research did not examine the timing of heat-diabetes associations and relation with comorbidities/risk factors. OBJECTIVE: We examined the association between heat exposure and diabetes-related hospitalizations in the transitional and summer months and identified populations vulnerable to heat. METHODS: We conducted a time-stratified case-crossover study. Data on diabetes hospital admissions (primary diagnosis of type 1 and type 2 diabetes, 2013-2020) were collected by the New York State (NYS) Department of Health under the state legislative mandate. We treated temperature and air pollutants as continuous variables and defined the heat exposure as per interquartile range (IQR, a measure between the 25th and 75th percentiles) increase of daily mean temperature. Conditional logistic regressions were performed to quantify the heat-diabetes associations after controlling for air pollutants and time variant variables. Multiplicative-scale interactions between heat and demographics/comorbidities/risk factors on diabetes hospitalizations were investigated. RESULTS: Each IQR increase in temperature was associated with significantly increased risks for diabetes admissions that occurred immediately and lasted for an entire week during multi-day lags in the transitional month of May (ranges of excess risk: 3.1 %-4.8 %) but not in the summer (June-August) (ranges of excess risk: -0.3 %-1.3 %). The significant increases in the excess risk of diabetes were also found among diabetes patients with complications of neuronopathy (excess risk: 27.7 %) and hypoglycemia (excess risk: 19.1 %). Furthermore, the modification effects on the heat-diabetes association were significantly stronger in females, Medicaid enrollees, non-compliant patients, and individuals with comorbidities of atherosclerotic heart disease and old myocardial infarction. CONCLUSIONS: Ambient heat exposure significantly increased the burden of hospital admissions for diabetes in transitional rather than summer months indicating the importance of exposure timing. Vulnerability to heat varied by demographics and heart comorbidity.

Synoptic weather typing applied to air pollution mortality among the elderly in 10 Canadian cities.

BACKGROUND: Synoptic circulation patterns (large-scale weather systems) affect ambient levels of air pollution, as well as the relationship between air pollution and human health. OBJECTIVE: To investigate the air pollution-mortality relationship within weather types and seasons, and to determine which combination of atmospheric conditions may pose increased health threats in the elderly age categories. METHODS: The relative risk of mortality (RR) due to air pollution was examined using Poisson generalized linear models (GLMs) within specific weather types. Analysis was completed by weather type and age group (all ages, ≤64, 65-74, 75-84, ≥85 years) in ten Canadian cities from 1981 to 1999. RESULTS: There was significant modification of RR by weather type and age. When examining the entire population, weather type was shown to have the greatest modifying effect on the risk of dying due to ozone (O3). This effect was highest on average for the dry tropical (DT) weather type, with the all-age RR of mortality at a population weighted mean (PWM) found to be 1.055 (95% CI 1.026-1.085). All-weather type risk estimates increased with age due to exposure to carbon monoxide (CO), nitrogen dioxide (NO2), and sulphur dioxide (SO2). On average, RR increased by 2.6, 3.8 and 1.5% for the respective pollutants between the ≤64 and ≥85 age categories. Conversely, mean ozone estimates remained relatively consistent with age. Elevated levels of air pollution were found to be detrimental to the health of elderly individuals for all weather types. However, the entire population was negatively effected by air pollution on the hot dry (DT) and hot humid (MT) days. CONCLUSIONS: We identified a significant modification of RR for mortality due to air pollution by age, which is enhanced under specific weather types. Efforts should be targeted at minimizing pollutant exposure to the elderly and/or all age groups with respect to weather type in question.