Quantifying Prescribed-Fire Smoke Exposure Using Low-Cost Sensors and Satellites: Springtime Burning in Eastern Kansas

Prescribed fires (fires intentionally set for mitigation purposes) produce pollutants, which have negative effects on human and animal health. One of the pollutants produced from fires is fine particulate matter (PM2.5). The Flint Hills (FH) region of Kansas experiences extensive prescribed burning each spring (March-May). Smoke from prescribed fires is often understudied due to a lack of monitoring in the rural regions where prescribed burning occurs, as well as the short duration and small size of the fires. Our goal was to attribute PM2.5 concentrations to the prescribed burning in the FH. To determine PM2.5 increases from local burning, we used low-cost PM2.5 sensors (PurpleAir) and satellite observations. The FH were also affected by smoke transported from fires in other regions during 2022. We separated the transported smoke from smoke from fires in eastern Kansas. Based on data from the PurpleAir sensors, we found the 24-hr median PM2.5 to increase by 3.0-5.3 μg m-3 (based on different estimates) on days impacted by smoke from fires in the eastern Kansas region compared to days unimpacted by smoke. The FH region was the most impacted by smoke PM2.5 compared to other regions of Kansas, as observed in satellite products and in situ measurements. Additionally, our study found that hourly PM2.5 estimates from a satellite-derived product aligned with our ground-based measurements. Satellite-derived products are useful in rural areas like the FH, where monitors are scarce, providing important PM2.5 estimates.

Reversal of trends in global fine particulate matter air pollution

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM_2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM_2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM_2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM_2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM_2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM_2.5 (>95 μg/m³). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

A cross-sectional analysis of ambient fine particulate matter (PM2.5) exposure and haemoglobin levels in children aged under 5 years living in 36 countries

Low haemoglobin (Hb) concentrations and anaemia in children have adverse effects on development and functioning, some of which may have consequences in later life. Exposure to ambient air pollution is reported to be associated with anaemia, but there is little evidence specific to low- and middle-income countries (LMICs), where childhood anaemia prevalence is greatest. We aimed to determine if long-term ambient fine particulate matter (≤2.5 μm in aerodynamic diameter [PM_2.5]) exposure was associated with Hb levels and the prevalence of anaemia in children aged <5 years living in 36 LMICs. We used Demographic and Health Survey data, collected between 2010 and 2019, which included blood Hb measurements. Satellite-derived estimates of annual average PM_2.5 was the main exposure variable, which was linked to children's area of residence. Anaemia was defined according to standard World Health Organization guidelines (Hb < 11 g/dL). The association of PM_2.5 with Hb levels and anaemia prevalence was examined using multivariable linear and logistic regression models, respectively. We examined whether the effects of ambient PM_2.5 were modified by a child's sex and age, household wealth index, and urban/rural place of residence. Models were adjusted for relevant covariates, including other outdoor pollutants and household cooking fuel. The study included 154,443 children, of which 89,904 (58.2%) were anaemic. The country-level prevalence of anaemia ranged from 15.8% to 87.9%. Mean PM_2.5 exposure was 33.0 (±21.6) μg/m³. The adjusted model showed that a 10 μg/m³ increase in annual PM_2.5 concentration was associated with greater odds of anaemia (OR = 1.098 95% CI: 1.087, 1.109). The same increase in PM_2.5 was associated with a decrease in average Hb levels of 0.075 g/dL (95% CI: 0.081, 0.068). There was evidence of effect modification by household wealth index and place of residence, with greater adverse effects in children from lower wealth quintiles and children in rural areas. Exposure to annual PM_2.5 was cross-sectionally associated with decreased blood Hb levels, and greater risk of anaemia, in children aged <5 years living in 36 LMICs.

A cross-sectional analysis of long-term exposure to ambient air pollution and cognitive development in children aged 3-4 years living in 12 low- and middle-income countries

Exposure to ambient air pollution may affect cognitive functioning and development in children. Unfortunately, there is little evidence available for low- and middle-income countries (LMICs), where air pollution levels are highest. We analysed the association between exposure to ambient fine particulate matter (≤2.5 μm [PM_2.5]) and cognitive development indicators in a cross-sectional analysis of children (aged 3-4 years) in 12 LMICs. We linked Demographic and Health Survey data, conducted between 2011 and 2018, with global estimates of PM_2.5 mass concentrations to examine annual average exposure to PM_2.5 and cognitive development (literacy-numeracy and learning domains) in children. Cognitive development was assessed using the United Nations Children's Fund's early child development indicators administered to each child's mother. We used multivariable logistic regression models, adjusted for individual- and area-level covariates, and multi-pollutant models (including nitrogen dioxide and surface-level ozone). We assessed if sex and urban/rural status modified the association of PM_2.5 with the outcome. We included 57,647 children, of whom, 9613 (13.3%) had indicators of cognitive delay. In the adjusted model, a 5 μg/m³ increase in annual all composition PM_2.5 was associated with greater odds of cognitive delay (OR = 1.17; 95% CI: 1.13, 1.22). A 5 μg/m³ increase in anthropogenic PM_2.5 was also associated with greater odds of cognitive delay (OR = 1.05; 95% CI: 1.00, 1.10). These results were robust to several sensitivity analyses, including multi-pollutant models. Interaction terms showed that urban-dwelling children had greater odds of cognitive delay than rural-dwelling children, while there was no significant difference by sex. Our findings suggest that annual average exposure to PM_2.5 in young children was associated with adverse effects on cognitive development, which may have long-term consequences for educational attainment and health.

Effects of long-term ambient air pollution exposure on township-level pulmonary tuberculosis notification rates during 2005-2017 in Ningxia, China

Studies examining long-term effects of ambient air pollution exposure, measured as annual averages, on pulmonary tuberculosis (TB) incidence are scarce, particularly in endemic, rural settings. We performed a small-area study in Ningxia Hui Autonomous Region (NHAR), a high TB-burden area in rural China, using township-level (n = 358 non-overlapping townships) annual TB notification data (2005-2017). We aimed to determine if annual average concentrations of ambient air pollution (particulate matter <2·5 μm [PM_2·5], nitrogen dioxide [NO₂] ozone [O₃]) were associated with TB notification rates (as a proxy for incidence). Air pollution effects on TB notification rates at township-level were estimated as incidence rate ratios (IRR), fitted using a generalised estimating equation (GEE) adjusted for covariates (age, sex, occupation, education, ethnicity, remoteness [urban or rural], household crowding and solid fuel use). A total of 38,942 TB notifications were reported in NHAR between 2005 and 2017. The mean annual TB notification rate was 67 (standard deviation [SD]; 7) per 100,000 people. Median concentrations of PM_2·5, NO₂, and O₃ were 42 μg/m³ (interquartile range [IQR]; 38-48 μg/m³), 15 ppb (IQR; 12-16 ppb), and 56 ppb (IQR; 56-57 ppb), respectively. In single pollutant models, adjusted for covariates, an interquartile range (IQR) increase (10 μg/m³) in PM_2·5 was significantly associated with higher TB notification rates (IRR: 1∙35; 95% CI: 1·25-1·48). Comparable effects on notifications of TB were observed for increases in NO₂ exposure (IRR: 1·20 per IQR (4 ppb) increase; 95% CI: 1·08-1·31). Ground-level ozone was not associated with TB notification rate in any models. The observed effects were consistent over time, in multi-pollutant models, and appeared robust to additional adjustment for indicators of household crowding, solid fuel use and remoteness. More rigorous study designs are needed to understand if improving air quality has population-level benefits on TB disease incidence in endemic settings.

Disparities in Air Pollutants Across Racial, Ethnic, and Poverty Groups at US Public Schools

We investigate socioeconomic disparities in air quality at public schools in the contiguous US using high resolution estimates of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations. We find that schools with higher proportions of people of color (POC) and students eligible for the federal free or reduced lunch program, a proxy for poverty level, are associated with higher pollutant concentrations. For example, we find that the median annual NO₂ concentration for White students, nationally, was 7.7 ppbv, compared to 9.2 ppbv for Black and African American students. Statewide and regional disparities in pollutant concentrations across racial, ethnic, and poverty groups are consistent with nationwide results, where elevated NO₂ concentrations were associated with schools with higher proportions of POC and higher levels of poverty. Similar, though smaller, differences were found in PM_2.5 across racial and ethnic groups in most states. Racial, ethnic, and economic segregation across the rural-urban divide is likely an important factor in pollution disparities at US public schools. We identify distinct regional patterns of disparities, highlighting differences between California, New York, and Florida. Finally, we highlight that disparities exist not only across urban and non-urban lines but also within urban environments.

Global urban temporal trends in fine particulate matter (PM2·5) and attributable health burdens: estimates from global datasets

BACKGROUND

With much of the world's population residing in urban areas, an understanding of air pollution exposures at the city level can inform mitigation approaches. Previous studies of global urban air pollution have not considered trends in air pollutant concentrations nor corresponding attributable mortality burdens. We aimed to estimate trends in fine particulate matter (PM_2·5) concentrations and associated mortality for cities globally.

METHODS

We use high-resolution annual average PM_2·5 concentrations, epidemiologically derived concentration response functions, and country-level baseline disease rates to estimate population-weighted PM_2·5 concentrations and attributable cause-specific mortality in 13 160 urban centres between the years 2000 and 2019.

FINDINGS

Although regional averages of urban PM_2·5 concentrations decreased between the years 2000 and 2019, we found considerable heterogeneity in trends of PM_2·5 concentrations between urban areas. Approximately 86% (2·5 billion inhabitants) of urban inhabitants lived in urban areas that exceeded WHO's 2005 guideline annual average PM_2·5 (10 μg/m³), resulting in an excess of 1·8 million (95% CI 1·34 million-2·3 million) deaths in 2019. Regional averages of PM_2·5-attributable deaths increased in all regions except for Europe and the Americas, driven by changes in population numbers, age structures, and disease rates. In some cities, PM_2·5-attributable mortality increased despite decreases in PM_2·5 concentrations, resulting from shifting age distributions and rates of non-communicable disease.

INTERPRETATION

Our study showed that, between the years 2000 and 2019, most of the world's urban population lived in areas with unhealthy levels of PM_2·5, leading to substantial contributions to non-communicable disease burdens. Our results highlight that avoiding the large public health burden from urban PM_2·5 will require strategies that reduce exposure through emissions mitigation, as well as strategies that reduce vulnerability to PM_2·5 by improving overall public health.

FUNDING

NASA, Wellcome Trust.

Maternal exposure to fine particulate matter and preterm birth and low birth weight in Africa

BACKGROUND

Fine particulate matter (PM_2.5) exposure has been reported to adversely affect birth outcomes, but the evidence is limited, particularly in low- and middle-income countries (LMICs). We assessed the associations between maternal PM_2.5 exposure and low birth weight (LBW) and preterm birth (PTB) in Africa.

METHODS

We used standard Demographic and Health Surveys (DHS) data (2005-2015) from 15 countries in Africa to conduct a cross-sectional study. The study population was composed of 131,594 births with detailed information on maternal and household variables. LBW was defined as a birth weight of < 2500 g after 37 weeks, and PTB was defined as live birth occurring before 37 weeks of gestation. Average exposure to PM_2.5 during pregnancy was estimated using satellite-based models. Multivariable logistic regression models were constructed, and analyses of data by region (Western, Eastern, Central, and Southern Africa) and data stratified by potential effect modifiers were conducted.

RESULTS

A total of 13,214 (10%) LBW and 4,377 (3.3%) PTB cases were identified. An interquartile range (IQR) (33.9 μg/m³) increase in PM_2.5 during pregnancy was associated with increased odds of LBW and PTB, with odds ratios (ORs) of 1.28 (95% CI: 1.23, 1.34) and 1.08 (95% CI: 1.01, 1.16), respectively. Region-specific analyses revealed significant associations between PM_2.5 and LBW in all regions, and significant associations between PM_2.5 and PTB in Western and Southern Africa. Subgroup analyses revealed that the association between PM_2.5 and LBW was present in all subgroups, and stronger associations were observed in female infants, while the association between PM_2.5 and PTB was larger in subgroups of older individuals living in urban areas.

CONCLUSION

This multicountry study in Africa demonstrated significant associations between maternal exposure to PM_2.5 and higher odds of LBW and PTB. Our findings may facilitate air quality control strategies that address adverse birth outcomes in LMICs.

Ambient air pollution and acute respiratory infection in children aged under 5 years living in 35 developing countries

BACKGROUND

Evidence from developed countries suggests that fine particulate matter (≤2.5 µm [PM_2.5]) contributes to childhood respiratory morbidity and mortality. However, few analyses have focused on resource-limited settings, where much of this burden occurs. We aimed to investigate the cross-sectional associations between annual average exposure to ambient PM_2.5 and acute respiratory infection (ARI) in children aged <5 years living in low- and middle-income countries (LMICs).

METHODS

We combined Demographic and Health Survey (DHS) data from 35 countries with gridded global estimates of annual PM_2.5 mass concentrations. We analysed the association between PM_2.5 and maternal-reported ARI in the two weeks preceding the survey among children aged <5 years living in 35 LMICs. We used multivariable logistic regression models that adjusted for child, maternal, household and cluster-level factors. We also fitted multi-pollutant models (adjusted for nitrogen dioxide [NO₂] and surface-level ozone [O₃]), among other sensitivity analyses. We assessed whether the associations between PM_2.5 and ARI were modified by sex, age and place of residence.

RESULTS

The analysis comprised 573,950 children, among whom the prevalence of ARI was 22,506 (3.92%). The mean (±SD) estimated annual concentration of PM_2.5 to which children were exposed was 48.2 (±31.0) µg/m³. The 5th and 95th percentiles of PM_2.5 were 9.8 µg/m³ and 110.9 µg/m³, respectively. A 10 µg/m³ increase in PM_2.5 was associated with greater odds of having an ARI (OR: 1.06; 95% CI: 1.05-1.07). The association between PM_2.5 and ARI was robust to adjustment for NO₂ and O₃. We observed evidence of effect modification by sex, age and place of residence, suggesting greater effects of PM_2.5 on ARI in boys, in younger children, and in children living in rural areas.

CONCLUSIONS

Annual average ambient PM_2.5, as an indicator for long-term exposure, was associated with greater odds of maternal-reported ARI in children aged <5 years living in 35 LMICs. Longitudinal studies in LMICs are required to corroborate our cross-sectional findings, to further elucidate the extent to which lowering PM_2.5 may have a role in the global challenge of reducing ARI-related morbidity and mortality in children.

Accelerated reduction of air pollutants in China, 2017-2020

Emission regulations of the power and industry sectors have been identified as the major driver of PM_2.5 mitigation over China during 2013-2017. In this study, we use ground-based observations of four air pollutants (CO, NO₂, SO₂, and PM_2.5) to show that additional stringent emission policies on the industrial, transportation, and residential sectors during the new 3-year protection plan (2018-2020) have accelerated the improvement of China's air quality. Based on regional (North and South China) trends of annual mean measurements, significant reductions are observed for all four pollutants during 2017-2020. These decreasing trends are found to be >30% stronger than 2015-2017 for NO₂, CO, and PM_2.5. For CO and PM_2.5, the acceleration is the strongest in winter and North China, when and where the residential clean-heating actions were implemented. While for NO₂, the accelerations are pronounced regardless of region or season, reflecting nationwide measures to reduce NO_x emissions from industrial and transportation activities. SO₂ concentration reductions that were already substantial before 2017 are maintained but not accelerated, consistent with the dominance of end-of-pipe measures rather than a structural change of energy fuels. Our investigation highlights the value of multi-pollutant analysis to relate emission policies with air quality changes.

Global fine-scale changes in ambient NO2 during COVID-19 lockdowns

Nitrogen dioxide (NO2) is an important contributor to air pollution and can adversely affect human health1-9. A decrease in NO2 concentrations has been reported as a result of lockdown measures to reduce the spread of COVID-1910-20. Questions remain, however, regarding the relationship of satellite-derived atmospheric column NO2 data with health-relevant ambient ground-level concentrations, and the representativeness of limited ground-based monitoring data for global assessment. Here we derive spatially resolved, global ground-level NO2 concentrations from NO2 column densities observed by the TROPOMI satellite instrument at sufficiently fine resolution (approximately one kilometre) to allow assessment of individual cities during COVID-19 lockdowns in 2020 compared to 2019. We apply these estimates to quantify NO2 changes in more than 200 cities, including 65 cities without available ground monitoring, largely in lower-income regions. Mean country-level population-weighted NO2 concentrations are 29% ± 3% lower in countries with strict lockdown conditions than in those without. Relative to long-term trends, NO2 decreases during COVID-19 lockdowns exceed recent Ozone Monitoring Instrument (OMI)-derived year-to-year decreases from emission controls, comparable to 15 ± 4 years of reductions globally. Our case studies indicate that the sensitivity of NO2 to lockdowns varies by country and emissions sector, demonstrating the critical need for spatially resolved observational information provided by these satellite-derived surface concentration estimates.

Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty

Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM2.5 concentrations exceed 90 μg/m3, with local concentrations of approximately 200 μg/m3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 μg/m3/year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.

Fine particulate matter constituents and infant mortality in Africa: A multicountry study

BACKGROUND

Few studies have investigated the association between exposure to fine particulate matter (PM_2.5) and infant mortality in developing countries, especially for the health effects of specific PM_2.5 constituents.

OBJECTIVE

We aimed to examine the association of long-term exposure to specific PM_2.5 constituents with infant mortality in 15 African countries from 2005 to 2015.

METHODS

Based on the Demographic and Health Surveys (DHS) dataset, we included birth history records from 15 countries in Africa and conducted a multicountry cross-sectional study to examine the associations between specific PM_2.5 constituents and infant mortality. We estimated annual residential exposure using satellite-derived PM_2.5 for mass and a chemical transport model (GEOS-Chem) for its six constituents, including organic matter (OM), black carbon (BC), sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), and soil dust (DUST). Multivariable logistic regression analysis was employed by fitting single-constituent models, the constituent-PM_2.5 models, and the constituent-residual models. We also conducted stratified analyses by potential effect modifiers and examined the specific associations for each country.

RESULTS

We found positive and significant associations between PM_2.5 total mass and most of its constituents with infant mortality. In the single-constituent model, for an IQR increase in pollutant concentrations, the odds ratio (OR) of infant mortality was 1.03 (95 %CI; 1.01, 1.06) for PM_2.5 total mass, and was 1.04 (95 %CI: 1.02, 1.06), 1.04 (95 %CI: 1.02, 1.05), 1.02 (95 %CI: 1.00, 1.03), 1.04 (1.01, 1.06) for BC, OM, SO₄^2-, and DUST, respectively. The associations of BC, OM, and SO₄^2- remained significant in the other two models. We observed larger estimates in subgroups with older maternal age, living in urban areas, using unclean cooking energy, and with access to piped water. The associations varied among countries, and by different constituents.

CONCLUSIONS

The carbonaceous fractions and sulfate play a major important role among PM_2.5 constituents on infant mortality. Our findings have certain policy implications for implementing effective measures for targeted reduction in specific sources (fossil fuel combustion and biomass burning) of PM_2.5 constituents against the risk of infant mortality.

Effects of COVID-19 lockdowns on fine particulate matter concentrations

Lockdowns during the COVID-19 pandemic provide an unprecedented opportunity to examine the effects of human activity on air quality. The effects on fine particulate matter (PM2.5) are of particular interest, as PM2.5 is the leading environmental risk factor for mortality globally. We map global PM2.5 concentrations for January to April 2020 with a focus on China, Europe, and North America using a combination of satellite data, simulation, and ground-based observations. We examine PM2.5 concentrations during lockdown periods in 2020 compared to the same periods in 2018 to 2019. We find changes in population-weighted mean PM2.5 concentrations during the lockdowns of -11 to -15 μg/m3 across China, +1 to -2 μg/m3 across Europe, and 0 to -2 μg/m3 across North America. We explain these changes through a combination of meteorology and emission reductions, mostly due to transportation. This work demonstrates regional differences in the sensitivity of PM2.5 to emission sources.

Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease.

METHODS

GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk-outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk-outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk-outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden.

FINDINGS

The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51-12·1) deaths (19·2% [16·9-21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12-9·31) deaths (15·4% [14·6-16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253-350) DALYs (11·6% [10·3-13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0-9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10-24 years, alcohol use for those aged 25-49 years, and high systolic blood pressure for those aged 50-74 years and 75 years and older.

INTERPRETATION

Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public.

FUNDING

Bill & Melinda Gates Foundation.

Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018)

Exposure to outdoor fine particulate matter (PM_2.5) is a leading risk factor for mortality. We develop global estimates of annual PM_2.5 concentrations and trends for 1998-2018 using advances in satellite observations, chemical transport modeling, and ground-based monitoring. Aerosol optical depths (AODs) from advanced satellite products including finer resolution, increased global coverage, and improved long-term stability are combined and related to surface PM_2.5 concentrations using geophysical relationships between surface PM_2.5 and AOD simulated by the GEOS-Chem chemical transport model with updated algorithms. The resultant annual mean geophysical PM_2.5 estimates are highly consistent with globally distributed ground monitors (R² = 0.81; slope = 0.90). Geographically weighted regression is applied to the geophysical PM_2.5 estimates to predict and account for the residual bias with PM_2.5 monitors, yielding even higher cross validated agreement (R² = 0.90-0.92; slope = 0.90-0.97) with ground monitors and improved agreement compared to all earlier global estimates. The consistent long-term satellite AOD and simulation enable trend assessment over a 21 year period, identifying significant trends for eastern North America (-0.28 ± 0.03 μg/m³/yr), Europe (-0.15 ± 0.03 μg/m³/yr), India (1.13 ± 0.15 μg/m³/yr), and globally (0.04 ± 0.02 μg/m³/yr). The positive trend (2.44 ± 0.44 μg/m³/yr) for India over 2005-2013 and the negative trend (-3.37 ± 0.38 μg/m³/yr) for China over 2011-2018 are remarkable, with implications for the health of billions of people.

Trends in Chemical Composition of Global and Regional Population-Weighted Fine Particulate Matter Estimated for 25 Years

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem, downscaled to 0.1° × 0.1°) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM_2.5). Trends in observed and simulated population-weighted mean PM_2.5 composition over 1989-2013 are highly consistent for PM_2.5 (-2.4 vs -2.4%/yr), secondary inorganic aerosols (-4.3 vs -4.1%/yr), organic aerosols (OA, -3.6 vs -3.0%/yr) and black carbon (-4.3 vs -3.9%/yr) over North America, as well as for sulfate (-4.7 vs -5.8%/yr) over Europe. Simulated trends over 1998-2013 also have overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM_2.5 for 20 of 21 global regions. Over 1989-2013, most (79%) of the simulated increase in global population-weighted mean PM_2.5 of 0.28 μg m^-3yr^-1 is explained by significantly (p < 0.05) increasing OA (0.10 μg m^-3yr^-1), nitrate (0.05 μg m^-3yr^-1), sulfate (0.04 μg m^-3yr^-1), and ammonium (0.03 μg m^-3yr^-1). These four components predominantly drive trends in population-weighted mean PM_2.5 over populous regions of South Asia (0.94 μg m^-3yr^-1), East Asia (0.66 μg m^-3yr^-1), Western Europe (-0.47 μg m^-3yr^-1), and North America (-0.32 μg m^-3yr^-1). Trends in area-weighted mean and population-weighted mean PM_2.5 composition differ significantly.

Anticholinergic medicines in an older primary care population: a cross-sectional analysis of medicines' levels of anticholinergic activity and clinical indications

WHAT IS KNOWN AND OBJECTIVES

Adverse clinical outcomes have been associated with cumulative anticholinergic burden (to which low-potency as well as high-potency anticholinergic medicines contribute). The clinical indications for which anticholinergic medicines are prescribed (and thus the 'phenotype' of patients with anticholinergic burden) have not been established. We sought to establish the overall prevalence of prescribing of anticholinergic medicines, the prevalence of prescribing of low-, medium- and high-potency anticholinergic medicines, and the clinical indications for which the medicines were prescribed in an older primary care population.

METHODS

This was a cross-sectional analysis of a cohort study of Australian early-career general practitioners' (GPs') clinical consultations - the Registrar Clinical Encounters in Training (ReCEnT) study. In ReCEnT, GPs collect detailed data (including medicines prescribed and their clinical indication) for 60 consecutive patients, on up to three occasions 6 months apart. Anticholinergic medicines were categorized as levels 1 (low-potency) to 3 (high-potency) using the Anticholinergic Drug Scale (ADS).

RESULTS

During 2010-2014, 879 early-career GPs (across five of Australia's six states) conducted 20 555 consultations with patients aged 65 years or older, representing 35 506 problems/diagnoses. Anticholinergic medicines were prescribed in 10·4% [95% CIs 9·5-10·5] of consultations. Of the total anticholinergic load of prescribed medicines ('community anticholinergic load') 72·7% [95% CIs 71·0-74·3] was contributed by Level 1 medicines, 0·8% [95% CIs 0·5-1·3] by Level 2 medicines and 26·5% [95% CIs 24·8-28·1] by Level 3 medicines. Cardiac (40·0%), Musculoskeletal (16·9%) and Respiratory (10·6%) were the most common indications associated with Level 1 anticholinergic prescription. For Level 2 and 3 medicines (combined data), Psychological (16·1%), Neurological (16·1%), Musculoskeletal (15·7%) and Urological (11·1%) indications were most common.

WHAT IS NEW AND CONCLUSION

Anticholinergic medicines are frequently prescribed in Australian general practice, and the majority of the 'community' anticholinergic burden is contributed by 'low'-anticholinergic potency medicines whose anticholinergic effects may be largely 'invisible' to prescribing GPs. Furthermore, the clinical 'phenotype' of the patient with high anticholinergic burden may be very different to common stereotypes (patients with urological, psychological or neurological problems), potentially making recognition of risk of anticholinergic adverse effects additionally problematic for GPs.

Secretin and autism: a two-part clinical investigation

Recent anecdotal reports have touted the gastrointestinal (GI) hormone secretin as a treatment modality for autism, though there is little clinical evidence or literature to support its viability. We undertook a two-part clinical trial to investigate these claims. Fifty-six patients (49 boys, 7 girls, mean age = 6.4 years, SD = 2.7) enrolled in an open-label trial of secretin, during which they received one injection of the hormone (2 IU/kg). All subjects were evaluated by their parents at baseline and follow-up visits (3-6 weeks later, M = 3.7, SD = 1.4 weeks) with Childhood Autism Rating Scales (CARS). Thirty-four patients were labeled with Pervasive Developmental Disorder Not Otherwise Specified, and 22 met diagnostic criteria for Autistic Disorder. Forty-five patients were concurrently on other drug treatments. At follow-up, some reported minimal but potentially significant improvements including changes in GI symptoms, expressive and/or receptive language function, and improved awareness and social interactions. No adverse effects were reported or observed. Subsequently, 17 of the most responsive patients from Study 1 began a double-blind trial that also included 8 newly enrolled patients. Patients in this second study were alternatively entered into one of two groups and received injections of secretin or placebo with crossover at 4 weeks. Patients from Study 1 entered into Study 2 at an average of 6.5 (SD = 0.8) weeks after beginning Study 1. Results of both inquiries indicate that although treatment with secretin was reported to cause transient changes in speech and behavior in some children, overall it produced few clinically meaningful changes when compared to children given placebo injections.

Clinical experience of three pediatric and one adult case of spike-and-wave status epilepticus treated with injectable valproic acid

Subclinical or nonconvulsive status epilepticus may cause severe postmorbid neurologic dysfunction. It is, therefore, critical to rapidly identify and treat these cases. The recent availability of injectable valproic acid (Depacon) provides an additional method for treatment of status epilepticus, although studies concerning its effectiveness are not widely available in the literature. We report four cases (three pediatric, one adult) of patients who presented to us in status epilepticus. All had previously failed more than one other common method of treatment for this condition. Treatment with injectable valproic acid resulted in the elimination of all clinical indications of status epilepticus as well as a return to the baseline EEG condition in all four cases. Seizure types included focal, multifocal, and generalized spike and wave forms, suggesting potential benefit from injectable valproic acid treatment in a wide range of status epilepticus patients. We present these cases for review.

Case study of institution-building by nurse Bertha Wright and colleagues

PURPOSE

To illuminate the history of nurses' participation in institution-building in the early 1900s, using the Baby Hospital in Oakland, California (now called Children's Hospital Oakland) as a case.

DESIGN

Historical research using a framework of women's history theory focused on the women who founded Oakland's Baby Hospital, 1910-1930.

METHOD

Data collection included studying original sources, archival material, and interviews. Data evaluation included external criticism for authenticity and genuineness, and internal criticism for accuracy and bias.

FINDINGS

In 1912, nurse Bertha Wright and social worker Mabel Weed, with a circle of community women, including Jessica Peixotto and Jean Howard McDuffie, established the Baby Hospital. Their activism included home visits, education, research, publications, political lobbying, and state policy and program development. At the center of this activity, was the lifelong commitment of Wright and Weed, who created new definitions of family. With social changes in the late 1920s, the male Board of Directors seized control of the hospital, and relegated women to auxiliary roles.

CONCLUSIONS

Health and social issues of the United States at the turn of the century are still problematic as a new century approaches and pertain to maternal-child health, foster care, and immigration. Feminists, including nurses, have played a central role in creating solutions. Knowledge of some of their incredible effort has been lost, particularly nursing's history in the western United States.

Outcome of children with opsoclonus-myoclonus regardless of etiology

Within the past 11 years, 11 patients with opsoclonus and myoclonus, with or without a history of neuroblastoma, have been admitted to Children's Memorial Hospital. Eight of the 11 children had an occult neuroblastoma. Eight children have had subsequent delayed development with motor incoordination and speech delay (7 with neuroblastoma, 1 without). Nine of 11 children initially were treated with ACTH, 1 child was treated with prednisone, and 1 was not treated. Nine of the 10 children who were treated had recurrences of symptoms during the gradual withdrawal or discontinuation of ACTH. Often the ACTH had to be restarted or increased, although several times the episodes were self-limited, not requiring treatment after ACTH was withdrawn. We found prednisone was ineffective in controlling opsoclonus-myoclonus regardless of etiology. The majority of children with opsoclonus-myoclonus, regardless of etiology, have developmental delay, more severe and at a higher rate than previously reported. When a neuroblastoma was present, tumor removal did not improve symptoms. Although limited in size, our study indicates patients with opsoclonus-myoclonus without an associated neuroblastoma have a better chance for normal neurologic development (2/3 versus 1/8).