Identifying Examinees Who Possess Distinct and Reliable Subscores When Added Value is Lacking for the Total Sample

Research has demonstrated that although subdomain information may provide no added value beyond the total score, in some contexts such information is of utility to particular demographic subgroups (Sinharay & Haberman, 2014). However, it is argued that the utility of reporting subscores for an individual should not be based on one’s manifest characteristics (e.g., gender or ethnicity), but rather on individual needs for diagnostic information, which is driven by multidimensionality in subdomain scores. To improve the validity of diagnostic information, this study proposed the use of Mahalanobis Distance and HT indices to assess whether an individual’s data significantly departs from unidimensionality. Those examinees that were found to differ significantly were then assessed separately for subscore added value via Haberman’s (2008) procedure. To this end, simulation analyses were conducted to evaluate Type I error, power, and recovery of subscore added value classifications for various levels of subdomain test lengths, subdomain inter-correlations, and proportions of multidimensionality in the total sample. Results demonstrated that the HT index possessed around 100% power across all conditions, while maintaining Type I error below 5%, which led to nearly perfect recovery of subscore added value classifications. In contrast, the power rates for Mahalanobis Distance were much lower ranging from 13% to 61% with Type I errors maintained at the nominal level of 5%. Although the power rates were below the desired criterion of 80%, the cases identified as aberrant using this method were found to have greater variability between subdomain scores, increased reliability, and lower observed subdomain correlations when compared to the generated data. As a result, outlier cases were found to have subscore added value for nearly 100% of cases across conditions even when the generated multidimensional data did not possess subscore added value. These results were cross-validated using a large-scale high-stakes test in which the Mahalanobis Distance measure was found to identify 6.57% of 8,803 test-takers that possessed subscores with added-value who otherwise would have been masked by the unidimensionality of the total sample. Overall, this study suggests that the Mahalanobis Distance measure shows some promise in identifying examinees with multidimensional score profiles

Observational Constraints on the Oxidation of NO_x in the Upper Troposphere

NO_x (NO_x ≡ NO + NO_2) regulates O_3 and HO_x (HO_x ≡ OH + HO_2) concentrations in the upper troposphere. In the laboratory, it is difficult to measure rates and branching ratios of the chemical reactions affecting NO_x at the low temperatures and pressures characteristic of the upper troposphere, making direct measurements in the atmosphere especially useful. We report quasi-Lagrangian observations of the chemical evolution of an air parcel following a lightning event that results in high NO_x concentrations. These quasi-Lagrangian measurements obtained during the Deep Convective Clouds and Chemistry experiment are used to characterize the daytime rates for conversion of NOx to different peroxy nitrates, the sum of alkyl and multifunctional nitrates, and HNO_3. We infer the following production rate constants [in (cm^3/molecule)/s] at 225 K and 230 hPa: 7.2(±5.7) × 10^(–12) (CH_3O_2NO_2), 5.1(±3.1) × 10^(–13) (HO_2NO_2), 1.3(±0.8) × 10^(–11) (PAN), 7.3(±3.4) × 10^(–12) (PPN), and 6.2(±2.9) × 10^(–12) (HNO_3). The HNO_3 and HO_2NO_2 rates are ∼30–50% lower than currently recommended whereas the other rates are consistent with current recommendations to within ±30%. The analysis indicates that HNO_3 production from the HO_2 and NO reaction (if any) must be accompanied by a slower rate for the reaction of OH with NO_2, keeping the total combined rate for the two processes at the rate reported for HNO_3 production above

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Emission Performance and User Acceptance of a Catalytic Biomass Cookstove in Rural Guatemala

A catalytic rocket stove was developed to reduce emissions and improve efficiency compared to open cooking fires or traditional semienclosed cookstoves, called poyos, typical of rural Guatemala. Traditional stoves often emit particulate matter and carbon monoxide at sufficient levels to cause respiratory illnesses and other health problems. Using focus group results, the stove was tailored to the needs of Guatemalan cooks. Field trial participants were provided with stove training to ensure that stoves were operated correctly. Somewhat surprisingly, the field trial demonstrated a high level of user acceptance in rural Guatemala, where users cooked 93% of the time with the catalytic stove despite having to change some cooking practices. In the field trial, the stove reduced emissions by as much as 68% and improved fuel efficiency by as much as 61% during real-world cooking events relative to the traditional poyo. An additional qualitative portion of the field study identified strengths and weaknesses of the stove that are being addressed as part of an iterative design process

Control of Toxic Chemicals in Puget Sound, Phase 3: Study of Atmospheric Deposition of Air Toxics to the Surface of Puget Sound

The results of the Phase 1 Toxics Loading study suggested that runoff from the land surface and atmospheric deposition directly to marine waters have resulted in considerable loads of contaminants to Puget Sound (Hart Crowser et al. 2007). The limited data available for atmospheric deposition fluxes throughout Puget Sound was recognized as a significant data gap. Therefore, this study provided more recent or first reported atmospheric deposition fluxes of PAHs, PBDEs, and select trace elements for Puget Sound. Samples representing bulk atmospheric deposition were collected during 2008 and 2009 at seven stations around Puget Sound spanning from Padilla Bay south to Nisqually River including Hood Canal and the Straits of Juan de Fuca. Revised annual loading estimates for atmospheric deposition to the waters of Puget Sound were calculated for each of the toxics and demonstrated an overall decrease in the atmospheric loading estimates except for polybrominated diphenyl ethers (PBDEs) and total mercury (THg). The median atmospheric deposition flux of total PBDE (7.0 ng/m2/d) was higher than that of the Hart Crowser (2007) Phase 1 estimate (2.0 ng/m2/d). The THg was not significantly different from the original estimates. The median atmospheric deposition flux for pyrogenic PAHs (34.2 ng/m2/d; without TCB) shows a relatively narrow range across all stations (interquartile range: 21.2- 61.1 ng/m2/d) and shows no influence of season. The highest median fluxes for all parameters were measured at the industrial location in Tacoma and the lowest were recorded at the rural sites in Hood Canal and Sequim Bay. Finally, a semi-quantitative apportionment study permitted a first-order characterization of source inputs to the atmosphere of the Puget Sound. Both biomarker ratios and a principal component analysis confirmed regional data from the Puget Sound and Straits of Georgia region and pointed to the predominance of biomass and fossil fuel (mostly liquid petroleum products such as gasoline and/or diesel) combustion as source inputs of combustion by-products to the atmosphere of the region and subsequently to the waters of Puget Sound

Pyrogenic Inputs of Anthropogenic Pb and Hg to Sediments of the Hood Canal, Washington, in the 20th Century: Source Evidence from Stable Pb Isotopes and PAH Signatures

Combustion-derived PAHs and stable Pb isotopic signatures (²⁰⁶Pb/²⁰⁷Pb) in sedimentary records assisted in reconstructing the sources of atmospheric inputs of anthropogenic Pb and Hg to the Hood Canal, Washington. The sediment-focusing corrected peak fluxes of total Pb and Hg (1960–70s) demonstrate that the watershed of Hood Canal has received greater atmospheric inputs of these metals than its mostly rural land use would predict. The tight relationships between the Pb, Hg, and organic markers in the cores indicate that these metals are derived from industrial combustion emissions. Multiple lines of evidence point to the Asarco smelter, located in the Main Basin of Puget Sound, as the major emission source of these metals to the watershed of the Hood Canal. The evidence includes (1) similar PAH isomer ratios in sediment cores from the two basins, (2) the correlations between Pb, Hg, and Cu in sediments and previously studied environmental samples including particulate matter emitted from the Asarco smelter’s main stack at the peak of production, and (3) Pb isotope ratios. The natural rate of recovery in Hood Canal since the 1970s, back to preindustrial metal concentrations, was linear and contrasts with recovery rates reported for the Main Basin which slowed post late 1980s

Small, Smart, Fast, and Cheap: Microchip-Based Sensors to Estimate Air Pollution Exposures in Rural Households

Over the last 20 years, the Kirk R. Smith research group at the University of California Berkeley—in collaboration with Electronically Monitored Ecosystems, Berkeley Air Monitoring Group, and other academic institutions—has developed a suite of relatively inexpensive, rugged, battery-operated, microchip-based devices to quantify parameters related to household air pollution. These devices include two generations of particle monitors; data-logging temperature sensors to assess time of use of household energy devices; a time-activity monitoring system using ultrasound; and a CO2-based tracer-decay system to assess ventilation rates. Development of each system involved numerous iterations of custom hardware, software, and data processing and visualization routines along with both lab and field validation. The devices have been used in hundreds of studies globally and have greatly enhanced our understanding of heterogeneous household air pollution (HAP) concentrations and exposures and factors influencing them

Small, Smart, Fast, and Cheap: Microchip-Based Sensors to Estimate Air Pollution Exposures in Rural Households.

Over the last 20 years, the Kirk R. Smith research group at the University of California Berkeley-in collaboration with Electronically Monitored Ecosystems, Berkeley Air Monitoring Group, and other academic institutions-has developed a suite of relatively inexpensive, rugged, battery-operated, microchip-based devices to quantify parameters related to household air pollution. These devices include two generations of particle monitors; data-logging temperature sensors to assess time of use of household energy devices; a time-activity monitoring system using ultrasound; and a CO₂-based tracer-decay system to assess ventilation rates. Development of each system involved numerous iterations of custom hardware, software, and data processing and visualization routines along with both lab and field validation. The devices have been used in hundreds of studies globally and have greatly enhanced our understanding of heterogeneous household air pollution (HAP) concentrations and exposures and factors influencing them