Large-scale agricultural burning and cardiorespiratory emergency department visits in the U.S. state of Kansas.

BACKGROUND: Prescribed agricultural burning is a common land management practice, but little is known about the health effects from the resulting smoke exposure. OBJECTIVE: To examine the association between smoke from prescribed burning and cardiorespiratory outcomes in the U.S. state of Kansas. METHODS: We analyzed a zip code-level, daily time series of primary cardiorespiratory emergency department (ED) visits for February-May (months when prescribed burning is common in Kansas) in the years 2009-2011 (n = 109,220). Given limited monitoring data, we formulated a measure of smoke exposure using non-traditional datasets, including fire radiative power and locational attributes from remote sensing data sources. We then assigned a population-weighted potential smoke impact factor (PSIF) to each zip code, based on fire intensity, smoke transport, and fire proximity. We used Poisson generalized linear models to estimate the association between PSIF on the same day and in the past 3 days and asthma, respiratory including asthma, and cardiovascular ED visits. RESULTS: During the study period, prescribed burning took place on approximately 8 million acres in Kansas. Same-day PSIF was associated with a 7% increase in the rate of asthma ED visits when adjusting for month, year, zip code, meteorology, day of week, holidays, and correlation within zip codes (rate ratio [RR]: 1.07; 95% confidence interval [CI]: 1.01, 1.13). Same-day PSIF was not associated with a combined outcome of respiratory ED visits (RR [95% CI]: 0.99 [0.97, 1.02]), or cardiovascular ED visits (RR [95% CI]: 1.01 [0.98, 1.04]). There was no consistent association between PSIF during the past 3 days and any of the outcomes. SIGNIFICANCE: These results suggest an association between smoke exposure and asthma ED visits on the same day. Elucidating these associations will help guide public health programs that address population-level exposure to smoke from prescribed burning.

Morbidity and Mortality of Unintentional Carbon Monoxide Poisoning: United States 2005 to 2018.

STUDY OBJECTIVE: Centers for Disease Control and Prevention conducts case surveillance through the National Notifiable Diseases Surveillance System (NNDSS). This study aimed to provide surveillance report of unintentional carbon monoxide poisoning across multiple data sources to provide baseline data for the new NNDSS carbon monoxide poisoning surveillance. METHODS: For the period 2005 to 2018, we used 4 data sources to describe unintentional carbon monoxide poisoning: exposures reported by poison centers, emergency department (ED) visits, hospitalizations, and deaths. We conducted descriptive analyses by the cause of exposure (fire, nonfire, or unknown), age, sex, season, and US census region. Additional analyses were conducted using poison center exposure case data focusing on the reported signs and symptoms, management site, and medical outcome. RESULTS: Annually, we observed 39.5 poison center exposure calls (per 1 million, nationally), 56.5 ED visits (per 1 million, across 17 states), 7.3 hospitalizations (per 1 million, in 26 states), and 3.3 deaths (per 1 million, nationally) due to unintentional carbon monoxide poisoning. For 2005 to 2018, there was a decrease in the crude rate for non-fire-related carbon monoxide poisonings from hospital, and death data. Non-fire-related cases comprised 74.0% of ED visits data, 60.1% of hospitalizations, and 40.9% of deaths compared with other unintentional causes. Across all data sources, unintentional carbon monoxide poisonings were most often reported during the winter season, notably in January and December. Children aged 0 to 9 years had the highest reported rates in poison center exposure case data and ED visits (54.1 and 70.5 per 1 million, respectively); adults older than 80 years had the highest rates of hospitalization and deaths (20.2 and 9.9 per 1 million, respectively); and deaths occurred more often among men and in the Midwest region. Poison center exposure call data revealed that 45.9% of persons were treated at a health care facility. Headaches, nausea, and dizziness/vertigo were the most reported symptoms. CONCLUSION: The crude rates in non-fire-related carbon monoxide poisonings from hospitalizations, and mortality significantly decreased over the study period (ie, 2005 to 2018). This surveillance report provides trends and characteristics of unintentional carbon monoxide poisoning and the baseline morbidities and mortality data for the Centers for Disease Control and Prevention national surveillance system of carbon monoxide poisoning.

Erratum: Paolo Lauriola et al., Advancing Global Health through Environmental and Public Health Tracking, Int. J. Environ. Res. Public Health 2020, 17, 1976.

Due to an error during production, some contents of Table 1 are missing in the published paper [...].

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters.

The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.

Smoke Alarms and Carbon Monoxide Alarms in Households With Children, Puerto Rico, 2010.

In 2017, Puerto Rico sustained extensive damage from Hurricane Maria, increasing the risk of fires and carbon monoxide (CO) poisonings. Using a population-based, in-person survey of households with children less than 6 years old in Puerto Rico, we collected data in 2010 concerning the presence of smoke alarms and CO alarms in these households. We generated national estimates by extrapolating the number of households in each stratum using data from the 2010 Census. We determined which household characteristics predicted the presence of these alarms. Of 355 households analyzed, 31% had functional smoke alarms, or an estimated 109,773 households territory wide. The presence of smoke alarms was associated with living in multifamily housing and no child in the household receiving government medical insurance. Public housing or publicly subsidized housing, as compared to owner-occupied housing and unsubsidized rental housing, was associated with having a functional smoke alarm in households with children aged less than 6 years. Based on only six houses having CO alarms, we estimated only 7685 (2%) households had CO alarms. The low prevalence of functional smoke or CO alarms 7 years before Hurricane Maria is unfortunate and should be remedied by ensuring that such alarms are widely installed in current rebuilding activities.

Availability, access, analysis and dissemination of small-area data.

In this era of 'big data', there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualizations, allowing small-area data to be seen and understood by non-expert audiences, are revolutionizing public and researcher interactions with data. The UK Small Area Health Statistics Unit's Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and 'mash-ups', and user-generated inputs from social media, mobile devices and wearable tech are new data streams that will find utility in future studies, and bring novel dimensions with respect to ethical use of small-area data.

Software application profile: the Rapid Inquiry Facility 4.0: an open access tool for environmental public health tracking.

The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants.

Advancing Global Health through Environmental and Public Health Tracking.

Global environmental change has degraded ecosystems. Challenges such as climate change, resource depletion (with its huge implications for human health and wellbeing), and persistent social inequalities in health have been identified as global public health issues with implications for both communicable and noncommunicable diseases. This contributes to pressure on healthcare systems, as well as societal systems that affect health. A novel strategy to tackle these multiple, interacting and interdependent drivers of change is required to protect the population's health. Public health professionals have found that building strong, enduring interdisciplinary partnerships across disciplines can address environment and health complexities, and that developing Environmental and Public Health Tracking (EPHT) systems has been an effective tool. EPHT aims to merge, integrate, analyse and interpret environmental hazards, exposure and health data. In this article, we explain that public health decision-makers can use EPHT insights to drive public health actions, reduce exposure and prevent the occurrence of disease more precisely in efficient and cost-effective ways. An international network exists for practitioners and researchers to monitor and use environmental health intelligence, and to support countries and local areas toward sustainable and healthy development. A global network of EPHT programs and professionals has the potential to advance global health by implementing and sharing experience, to magnify the impact of local efforts and to pursue data knowledge improvement strategies, aiming to recognise and support best practices. EPHT can help increase the understanding of environmental public health and global health, improve comparability of risks between different areas of the world including Low and Middle-Income Countries (LMICs), enable transparency and trust among citizens, institutions and the private sector, and inform preventive decision making consistent with sustainable and healthy development. This shows how EPHT advances global health efforts by sharing recent global EPHT activities and resources with those working in this field. Experiences from the US, Europe, Asia and Australasia are outlined for operating successful tracking systems to advance global health.

Public Perceptions of Environmental Public Health Risks in the United States.

Understanding public perceptions about environmental health hazards, exposures, and health impacts can help environmental public health practitioners to target and prioritize community activities, policy needs, and communication strategies. The online cross-sectional 2013 summer wave of the ConsumerStyles survey sampled U.S. adults and used questions from the Centers for Disease Control's Environmental Public Health Tracking Program to measure public awareness of governmental efforts to track environmental exposures and links to health impacts, as well as perceptions of environmental health issues. Unadjusted and adjusted logistic regressions examined the associations between demographic characteristics and level of awareness of government environmental public health efforts or level of concern about health risks associated with environmental pollutants. Responses were received from 4033 participants, yielding a response rate of 66.0%. More than half of respondents (57.8%) noted concerns about health risks from environmental pollutants. More than one-third (40.0%) of respondents reported awareness of government efforts. Nearly 40% of respondents felt that none of the health impacts listed in the survey were related to environmental issues. Multiple logistic regression models showed that non-Hispanic blacks, other races, females, people with a college or higher education, and people living in the Midwest or South regions were more likely than their counterparts to be concerned about how the environment affects their health. Future work should focus on improving risk communication, filling the information gap on environmental health issues, and understanding how perceptions change over time.

Air Quality Awareness Among U.S. Adults With Respiratory and Heart Disease.

INTRODUCTION: Poor air quality affects respiratory and cardiovascular health. Information about health risks associated with outdoor air quality is communicated to the public using air quality alerts. This study was conducted to assess associations of existing respiratory and heart disease with three aspects of air quality awareness: awareness of air quality alerts, discussing with a health professional strategies to reduce air pollution exposure, and avoiding busy roads to reduce air pollution exposure when walking, biking, or exercising outdoors. METHODS: During 2014-2016, a total of 12,599 U.S. adults participated in summer waves of the ConsumerStyles surveys and self-reported asthma, emphysema/chronic obstructive pulmonary disease, heart disease, and each aspect of air quality awareness. In 2017, associations between each health condition and air quality awareness were estimated using log binomial and multinomial regression. RESULTS: Overall, 49% of respondents were aware of air quality alerts, 3% discussed with a health professional strategies to reduce air pollution exposure, and 27% always/usually avoided busy roads to reduce air pollution exposure. Asthma was associated with increased prevalence of awareness of air quality alerts (prevalence ratio=1.11, 95% CI=1.04, 1.20), discussing with a health professional (prevalence ratio=4.88, 95% CI=3.74, 6.37), and always/usually avoiding busy roads to reduce air pollution exposure (prevalence ratio=1.13, 95% CI=1.01, 1.27). Heart disease was not associated with air quality awareness. CONCLUSIONS: Existing respiratory disease, but not heart disease, was associated with increased air quality awareness. These findings reveal important opportunities to raise awareness of air quality alerts and behavior changes aimed at reducing air pollution exposure among adults at risk of exacerbating respiratory and heart diseases.

Developing an online tool for identifying at-risk populations to wildfire smoke hazards.

Wildfire episodes pose a significant public health threat in the United States. Adverse health impacts associated with wildfires occur near the burn area as well as in places far downwind due to wildfire smoke exposures. Health effects associated with exposure to particulate matter arising from wildfires can range from mild eye and respiratory tract irritation to more serious outcomes such as asthma exacerbation, bronchitis, and decreased lung function. Real-time operational forecasts of wildfire smoke concentrations are available but they are not readily integrated with information on vulnerable populations necessary to identify at-risk communities during wildfire smoke episodes. Efforts are currently underway at the Centers for Disease Control and Prevention (CDC) to develop an online tool that utilizes short-term predictions and forecasts of smoke concentrations and integrates them with measures of population-level vulnerability for identifying at-risk populations to wildfire smoke hazards. The tool will be operationalized on a national scale, seeking input and assistance from several academic, federal, state, local, Tribal, and Territorial partners. The final product will then be incorporated into CDC's National Environmental Public Health Tracking Network (http://ephtracking.cdc.gov), providing users with access to a suite of mapping and display functionalities. A real-time vulnerability assessment tool incorporating standardized health and exposure datasets, and prevention guidelines related to wildfire smoke hazards is currently unavailable for public health practitioners and emergency responders. This tool could strengthen existing situational awareness competencies, and expedite future response and recovery efforts during wildfire episodes.

Rural and Urban Differences in Air Quality, 2008-2012, and Community Drinking Water Quality, 2010-2015 - United States.

PROBLEM/CONDITION: The places in which persons live, work, and play can contribute to the development of adverse health outcomes. Understanding the differences in risk factors in various environments can help to explain differences in the occurrence of these outcomes and can be used to develop public health programs, interventions, and policies. Efforts to characterize urban and rural differences have largely focused on social and demographic characteristics. A paucity of national standardized environmental data has hindered efforts to characterize differences in the physical aspects of urban and rural areas, such as air and water quality. REPORTING PERIOD: 2008-2012 for air quality and 2010-2015 for water quality. DESCRIPTION OF SYSTEM: Since 2002, CDC's National Environmental Public Health Tracking Program has collaborated with federal, state, and local partners to gather standardized environmental data by creating national data standards, collecting available data, and disseminating data to be used in developing public health actions. The National Environmental Public Health Tracking Network (i.e., the tracking network) collects data provided by national, state, and local partners and includes 21 health outcomes, exposures, and environmental hazards. To assess environmental factors that affect health, CDC analyzed three air-quality measures from the tracking network for all counties in the contiguous United States during 2008-2012 and one water-quality measure for 26 states during 2010-2015. The three air-quality measures include 1) total number of days with fine particulate matter (PM2.5) levels greater than the U.S. Environmental Protection Agency's (EPA's) National Ambient Air Quality Standards (NAAQS) for 24-hour average PM2.5 (PM2.5 days); 2) mean annual average ambient concentrations of PM2.5 in micrograms per cubic meter (mean PM2.5); and 3) total number of days with maximum 8-hour average ozone concentrations greater than the NAAQS (ozone days). The water-quality measure compared the annual mean concentration for a community water system (CWS) to the maximum contaminant level (MCL) defined by EPA for 10 contaminants: arsenic, atrazine, di(2-ethylhexyl) phthalate (DEHP), haloacetic acids (HAA5), nitrate, perchloroethene (PCE), radium, trichloroethene (TCE), total trihalomethanes (TTHM), and uranium. Findings are presented by urban-rural classification scheme: four metropolitan (large central metropolitan, large fringe metropolitan, medium metropolitan, and small metropolitan) and two nonmetropolitan (micropolitan and noncore) categories. Regression modeling was used to determine whether differences in the measures by urban-rural categories were statistically significant. RESULTS: Patterns for all three air-quality measures suggest that air quality improves as areas become more rural (or less urban). The mean total number of ozone days decreased from 47.54 days in large central metropolitan counties to 3.81 days in noncore counties, whereas the mean total number of PM2.5 days decreased from 11.21 in large central metropolitan counties to 0.95 in noncore counties. The mean average annual PM2.5 concentration decreased from 11.15 µg/m3 in large central metropolitan counties to 8.87 µg/m3 in noncore counties. Patterns for the water-quality measure suggest that water quality improves as areas become more urban (or less rural). Overall, 7% of CWSs reported at least one annual mean concentration greater than the MCL for all 10 contaminants combined. The percentage increased from 5.4% in large central metropolitan counties to 10% in noncore counties, a difference that was significant, adjusting for U.S. region, CWS size, water source, and potential spatial correlation. Similar results were found for two disinfection by-products, HAA5 and TTHM. Arsenic was the only other contaminant with a significant result. Medium metropolitan counties had 3.1% of CWSs reporting at least one annual mean greater than the MCL, compared with 2.4% in large central counties. INTERPRETATION: Noncore (rural) counties experienced fewer unhealthy air-quality days than large central metropolitan counties, likely because of fewer air pollution sources in the noncore counties. All categories of counties had a mean annual average PM2.5 concentration lower than the EPA standard. Among all CWSs analyzed, the number reporting one or more annual mean contaminant concentrations greater the MCL was small. The water-quality measure suggests that water quality worsens as counties become more rural, in regards to all contaminants combined and for the two disinfection by-products individually. Although significant differences were found for the water-quality measure, the odds ratios were very small, making it difficult to determine whether these differences have a meaningful effect on public health. These differences might be a result of variations in water treatment practices in rural versus urban counties. PUBLIC HEALTH ACTION: Understanding the differences between rural and urban areas in air and water quality can help public health departments to identify, monitor, and prioritize potential environmental public health concerns and opportunities for action. These findings suggest a continued need to develop more geographically targeted, evidence-based interventions to prevent morbidity and mortality associated with poor air and water quality.

Characterization of Carbon Monoxide Exposure During Hurricane Sandy and Subsequent Nor'easter.

OBJECTIVE: Carbon monoxide (CO) is an odorless, colorless gas produced by fossil fuel combustion. On October 29, 2012, Hurricane Sandy moved ashore near Atlantic City, New Jersey, causing widespread morbidity and mortality, $30 to $50 billion in economic damage, and 8.5 million households to be without power. The combination of power outages and unusually low temperatures led people to use alternate power sources, placing many at risk for CO exposure. METHODS: We examined Hurricane Sandy-related CO exposures from multiple perspectives to help identify risk factors and develop strategies to prevent future exposures. This report combined data from 3 separate sources (health departments, poison centers via the National Poison Data System, and state and local public information officers). RESULTS: Results indicated that the number of CO exposures in the wake of Hurricane Sandy was significantly greater than in previous years. The persons affected were mostly females and those in younger age categories and, despite messaging, most CO exposures occurred from improper generator use. CONCLUSIONS: Our findings emphasize the continued importance of CO-related communication and ongoing surveillance of CO exposures to support public health response and prevention during and after disasters. Additionally, regional poison centers can be a critical resource for potential on-site management, public health promotion, and disaster-related CO exposure surveillance. (Disaster Med Public Health Preparedness. 2017;11:562-567).

Assessment of traditional and improved stove use on household air pollution and personal exposures in rural western Kenya.

BACKGROUND: Over 40% of the world's population relies on solid fuels for heating and cooking. Use of improved biomass cookstoves (ICS) has the potential to reduce household air pollution (HAP). OBJECTIVES: As part of an evaluation to identify ICS for use in Kenya, we collected indoor air and personal air samples to assess differences between traditional cookstoves (TCS) and ICS. METHODS: We conducted a cross-over study in 2012 in two Kenyan villages; up to six different ICS were installed in 45 households during six two-week periods. Forty-eight hour kitchen measurements of fine particulate matter (PM2.5) and carbon monoxide (CO) were collected for the TCS and ICS. Concurrent personal CO measurements were conducted on the mother and one child in each household. We performed descriptive analysis and compared paired measurements between baseline (TCS only) and each ICS. RESULTS: The geometric mean of 48-hour baseline PM2.5 and CO concentrations in the kitchen was 586µg/m3 (95% CI: 460, 747) and 4.9ppm (95% CI: 4.3, 5.5), respectively. For each ICS, the geometric mean kitchen air pollutant concentration was lower than the TCS: median reductions were 38.8% (95% CI: 29.5, 45.2) for PM2.5 and 27.1% (95% CI: 17.4, 40.3) for CO, with statistically significant relationships for four ICS. We also observed a reduction in personal exposures to CO with ICS use. CONCLUSIONS: We observed a reduction in mean 48-hour PM2.5 and CO concentrations compared to the TCS; however, concentrations for both pollutants were still consistently higher than WHO air quality guidelines. Our findings illustrate that ICS tested in real-world settings can reduce exposures to HAP, but implementation of cleaner fuels and related stove technologies may also be necessary to optimize public health benefits.

Effectiveness of Six Improved Cookstoves in Reducing Household Air Pollution and Their Acceptability in Rural Western Kenya.

BACKGROUND: Household air pollution (HAP) from biomass fuel burning is linked to poor health outcomes. Improved biomass cookstoves (ICS) have the potential to improve HAP. OBJECTIVES: A pre-/post- intervention study assessed the impact of six ICS on indoor air quality and acceptability of ICS to local users in rural Western Kenya. METHODS: We measured mean personal and kitchen level concentrations of particulate matter <2.5µm in diameter (PM2.5, µg/m3) and carbon monoxide (CO, ppm) during the 48-hour period of each ICS use in 45 households. We compared these levels to those observed with traditional 3-stone fire (TSF) use. We assessed ICS acceptability through interviews and focus groups. We evaluated association of stove type, fuel use, and factors related to cooking practices with mean kitchen PM2.5 and CO using multivariable regression. RESULTS: Stove type, exclusive ICS use (vs. concurrent TSF use), and the amount of fuel used were independently associated with kitchen PM2.5 and CO levels. Reductions (95%CI) in mean PM2.5 compared to TSF, ranged by ICS from 11.9% (-2.8-24.5) to 42.3% (32.3-50.8). Reductions in kitchen CO compared to TSF, ranged by ICS from -5.8% (-21.9-8.2) to 34.5% (23.2-44.1). Mean kitchen PM2.5 ranged from 319µg/m3 to 518µg/m3 by ICS. Women thought ICS were easy to use, more efficient, produced less smoke, and cooked faster, compared to TSF. Women also reported limitations for each ICS. CONCLUSIONS: We documented reductions in HAP from ICS compared to TSF. The PM2.5 levels with ICS use were still considerably higher than WHO indoor air quality guidelines. Achieving maximal potential of ICS requires adherence to more exclusive use and addressing user reported ICS limitations.

Use of Temperature Sensors to Determine Exclusivity of Improved Stove Use and Associated Household Air Pollution Reductions in Kenya.

Household air pollution (HAP) contributes to 3.5-4 million annual deaths globally. Recent interventions using improved cookstoves (ICS) to reduce HAP have incorporated temperature sensors as stove use monitors (SUMs) to assess stove use. We deployed SUMs in an effectiveness study of 6 ICSs in 45 Kenyan rural homes. Stove were installed sequentially for 2 weeks and kitchen air monitoring was conducted for 48 h during each 2-week period. We placed SUMs on the ICSs and traditional cookstoves (TCS), and the continuous temperature data were analyzed using an algorithm to examine the number of cooking events, days of exclusive use of ICS, and how stove use patterns affect HAP. Stacking, defined as using both a TCS and an ICS in the same day, occurred on 40% of the study days, and exclusive use of the ICS occurred on 25% of study days. When researchers were not present, ICS use declined, which can have implications for long-term stove adoption in these communities. Continued use of TCSs was also associated with higher HAP levels. SUMs are a valuable tool for characterizing stove use and provide additional information to interpret HAP levels measured during ICS intervention studies.

Respiratory Health Effects of Ultrafine Particles in Children: A Literature Review.

By convention, airborne particles ≤0.1 µm (100 nm) are defined as ultrafine particles (UFPs). UFPs can comprise a large number of particles in particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5). Despite the documented respiratory health effects of PM2.5 and concerns that UFPs might be more toxic than larger particular matter, the effects of UFPs on the respiratory system are not well-described. Even less is known about the respiratory health effects of UFPs among particularly vulnerable populations including children. We reviewed studies examining respiratory health effects of UFPs in children and identified 12 relevant articles. Most (8/12) studies measured UFP exposure using central ambient monitors, and we found substantial heterogeneity in UFP definitions and study designs. No long-term studies were identified. In single pollutant models, UFPs were associated with incident wheezing, current asthma, lower spirometric values, and asthma-related emergency department visits among children. Also, higher exhaled nitric oxide levels were positively correlated with UFP dose among children with asthma or allergy to house dust mites in 1 study. Multivariate models accounting for potential co-pollutant confounding yielded no statistically significant results. Although evidence for a relationship between UFPs and children's respiratory is accumulating, the literature remains inconclusive. Interpretation of existing data is constrained by study heterogeneity, limited accounting for UFP spatial variation, and lack of significant findings from multi-pollutant models.

Short-term effects of ambient air pollutants on asthma-related emergency department visits in Indianapolis, Indiana, 2007-2011.

OBJECTIVE: We estimate the short-term associations between daily changes in ambient air pollutants and daily asthma-related emergency department (ED) visits in Indianapolis, IN. METHODS: We identified asthma-related ED visits among Indianapolis residents aged ≥5 years. We used Poisson regression in a time-series framework to estimate the increased risk for asthma-related ED visits from exposure to ambient SO2, PM2.5 and ozone during the warm season (April-September) and SO2 and PM2.5 during the cold (October-March) season, from 2007 to 2011. Our models controlled for measured confounders, including weather and respiratory infections, as well as unmeasured confounders using a natural cubic spline to account for long-term seasonal trends. RESULTS: During 2007-2011 in Indianapolis, 165,056 asthma-related ED visits occurred. We found statistically significant positive associations (p < 0.05) between ambient air pollutants and ED visits during the warm season for persons aged 5-44 years. Interquartile range increases in daily ozone concentrations with same day, 2-day lagged, and 3-day moving average were associated with increased risks for ED visits of 3.2% (95% CI: 0.2%, 6.3%), 4.4% (0.1%, 8.9%) and 4.8% (0.2%, 9.6%), respectively. Interquartile range increases in 3-day moving averages for SO2 were associated with an increased risk of 3.3% (95% CI: 0.2%, 6.5%). We identified statistically significant associations (p < 0.05) between increased SO2 and PM2.5 levels and decreased ED visits among some age groups, primarily during the cold season, and no significant positive associations between changes in PM2.5 concentration and asthma-related ED visits. CONCLUSIONS: During the warm season, increases in ozone and SO2 concentrations were associated with increased asthma morbidity in children and young adults in Indianapolis. These results will enable reliable estimation of the health impacts of increases in these pollutants on asthma-related ED visits in Indianapolis and similar communities.

Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston.

This paper continues an initiative conducted by the International Society for Disease Surveillance with funding from the Defense Threat Reduction Agency to connect near-term analytical needs of public health practice with technical expertise from the global research community. The goal is to enhance investigation capabilities of day-to-day population health monitors. A prior paper described the formation of consultancies for requirements analysis and dialogue regarding costs and benefits of sustainable analytic tools. Each funded consultancy targets a use case of near-term concern to practitioners. The consultancy featured here focused on improving predictions of asthma exacerbation risk in demographic and geographic subdivisions of the city of Boston, Massachusetts, USA based on the combination of known risk factors for which evidence is routinely available. A cross-disciplinary group of 28 stakeholders attended the consultancy on March 30-31, 2016 at the Boston Public Health Commission. Known asthma exacerbation risk factors are upper respiratory virus transmission, particularly in school-age children, harsh or extreme weather conditions, and poor air quality. Meteorological subject matter experts described availability and usage of data sources representing these risk factors. Modelers presented multiple analytic approaches including mechanistic models, machine learning approaches, simulation techniques, and hybrids. Health department staff and local partners discussed surveillance operations, constraints, and operational system requirements. Attendees valued the direct exchange of information among public health practitioners, system designers, and modelers. Discussion finalized design of an 8-year de-identified dataset of Boston ED patient records for modeling partners who sign a standard data use agreement.