Spatial Misalignment in time series studies of air pollution and health data

Time series studies of environmental exposures often involve comparing daily changes in a toxicant measured at a point in space with daily changes in an aggregate measure of health. Spatial misalignment of the exposure and response variables can bias the estimation of health risk and the magnitude of this bias depends on the spatial variation of the exposure of interest. In air pollution epidemiology, there is an increasing focus on estimating the health effects of the chemical components of particulate matter. One issue that is raised by this new focus is the spatial misalignment error introduced by the lack of spatial homogeneity in many of the particulate matter components. Current approaches to estimating short-term health risks via time series modeling do not take into account the spatial properties of the chemical components and therefore could result in biased estimation of those risks. We present a spatial-temporal statistical model for quantifying spatial misalignment error and show how adjusted heath risk estimates can be obtained using a regression calibration approach and a two-stage Bayesian model. We apply our methods to a database containing information on hospital admissions, air pollution, and weather for 20 large urban counties in the United States

The Use of a Quasi-Experimental Study on the Mortality Effect of a Heat Wave Warning System in Korea.

Many cities and countries have implemented heat wave warning systems to combat the health effects of extreme heat. Little is known about whether these systems actually reduce heat-related morbidity and mortality. We examined the effectiveness of heat wave alerts and health plans in reducing the mortality risk of heat waves in Korea by utilizing the discrepancy between the alerts and the monitored temperature. A difference-in-differences analysis combined with propensity score weighting was used. Mortality, weather monitoring, and heat wave alert announcement data were collected for 7 major cities during 2009-2014. Results showed evidence of risk reduction among people aged 19-64 without education (-0.144 deaths/1,000,000 people, 95% CI: -0.227, -0.061) and children aged 0-19 (-0.555 deaths/1,000,000 people, 95% CI: -0.993, -0.117). Decreased cardiovascular and respiratory mortality was found in several subgroups including single persons, widowed people, blue-collar workers, people with no education or the highest level of education (university or higher). No evidence was found for decreased all-cause mortality in the population (1.687 deaths/1,000,000 people per day; 95% CI: 1.118, 2.255). In conclusion, heat wave alerts may reduce mortality for several causes and subpopulations of age and socio-economic status. Further work needs to examine the pathways through which the alerts impact subpopulations differently

Time-Series Studies of Particulate Matter

Studies of air pollution and human health have evolved from descriptive studies of the early phenomena of large increases in adverse health effects following extreme air pollution episodes, to time-series analyses and the development of sophisticated regression models. In fact, advanced statistical methods are necessary to address the many challenges inherent in the detection of a small pollution risk in the presence of many confounders. This paper reviews the history, methods, and findings of the time-series studies estimating health risks associated with short-term exposure to particulate matter, though much of the discussion is applicable to epidemiological studies of air pollution in general. We review the critical role of epidemiological studies in setting regulatory standards and the history of PM epidemiology and time-series analysis. We also summarize recent time-series results and conclude with a discussion of current and future directions of time-series analysis of particulates, including research on mortality displacement and the resolution of results from cohort and time-series studies

Identification of senescence and death in Emiliania huxleyi and Thalassiosira pseudonana: Cell staining, chlorophyll alterations, and dimethylsulfoniopropionate (DMSP) metabolism

We measured membrane permeability, hydrolytic enzyme, and caspase-like activities using fluorescent cell stains to document changes caused by nutrient exhaustion in the coccolithophore Emiliania huxleyi and the diatom Thalassiosira pseudonana, during batch-culture nutrient limitation. We related these changes to cell death, pigment alteration, and concentrations of dimethylsulfide (DMS) and dimethylsulfoniopropionate (DMSP) to assess the transformation of these compounds as cell physiological condition changes. E. huxleyi persisted for 1 month in stationary phase; in contrast, T. pseudonana cells rapidly declined within 10 d of nutrient depletion. T. pseudonana progressively lost membrane integrity and the ability to metabolize 5-chloromethylfluorescein diacetate (CMFDA; hydrolytic activity), whereas E. huxleyi developed two distinct CMFDA populations and retained membrane integrity (SYTOX Green). Caspase-like activity appeared higher in E. huxleyi than in T. pseudonana during the post-growth phase, despite a lack of apparent mortality and cell lysis. Photosynthetic pigment degradation and transformation occurred in both species after growth; chlorophyll a (Chl a) degradation was characterized by an increase in the ratio of methoxy Chl a : Chl a in T. pseudonana but not in E. huxleyi, and the increase in this ratio preceded loss of membrane integrity. Total DMSP declined in T. pseudonana during cell death and DMS increased. In contrast, and in the absence of cell death, total DMSP and DMS increased in E. huxleyi. Our data show a novel chlorophyll alteration product associated with T. pseudonana death, suggesting a promising approach to discriminate nonviable cells in nature

Ozone and Mortality: A Meta-Analysis of Time-Series Studies and Comparison to a Multi-City Study (The National Morbidity, Mortality, and Air Pollution Study)

While many time-series studies of ozone and daily mortality identified positive associations,others yielded null or inconclusive results. We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups,cause-specific mortality, and concentration metrics. We compared results to estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. cities from 1987 to 2000. Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current day ozone exposure as compared to other single day lags. In both analyses, results were not sensitive to adjustment for particulate matter and model specifications. In the meta-analysis we found that a 10 ppb increase in daily ozone is associated with a 0.83 (95% confidence interval: 0.53, 1.12%) increase in total mortality, whereas the corresponding NMMAPS estimate is 0.25%(0.12, 0.39%). Meta-analysis results were consistently larger than those from NMMAPS,indicating publication bias. Additional publication bias is evident regarding the choice of lags in time-series studies, and the larger heterogeneity in posterior city-specific estimates in the meta-analysis, as compared with NMAMPS

Advancing our Understanding of Heat Wave Criteria and Associated Health Impacts to Improve Heat Wave Alerts in Developing Country Settings.

Health effects of heat waves with high baseline temperatures in areas such as India remain a critical research gap. In these regions, extreme temperatures may affect the underlying population's adaptive capacity; heat wave alerts should be optimized to avoid continuous high alert status and enhance constrained resources, especially under a changing climate. Data from registrars and meteorological departments were collected for four communities in Northwestern India. Propensity Score Matching (PSM) was used to obtain the relative risk of mortality and number of attributable deaths (i.e., absolute risk which incorporates the number of heat wave days) under a variety of heat wave definitions (n = 13) incorporating duration and intensity. Heat waves' timing in season was also assessed for potential effect modification. Relative risk of heat waves (risk of mortality comparing heat wave days to matched non-heat wave days) varied by heat wave definition and ranged from 1.28 [95% Confidence Interval: 1.11-1.46] in Churu (utilizing the 95th percentile of temperature for at least two consecutive days) to 1.03 [95% CI: 0.87-1.23] in Idar and Himmatnagar (utilizing the 95th percentile of temperature for at least four consecutive days). The data trended towards a higher risk for heat waves later in the season. Some heat wave definitions displayed similar attributable mortalities despite differences in the number of identified heat wave days. These findings provide opportunities to assess the "efficiency" (or number of days versus potential attributable health impacts) associated with alternative heat wave definitions. Findings on both effect modification and trade-offs between number of days identified as "heat wave" versus health effects provide tools for policy makers to determine the most important criteria for defining thresholds to trigger heat wave alerts

Heat-Related Mortality and Adaptation to Heat in the United States

Background: In a changing climate, increasing temperatures are anticipated to have profound health impacts. These impacts could be mitigated if individuals and communities adapt to changing exposures; however, little is known about the extent to which the population may be adapting. Objective: We investigated the hypothesis that if adaptation is occurring, then heat-related mortality would be decreasing over time. Methods: We used a national database of daily weather, air pollution, and age-stratified mortality rates for 105 U.S. cities (covering 106 million people) during the summers of 1987–2005. Time-varying coefficient regression models and Bayesian hierarchical models were used to estimate city-specific, regional, and national temporal trends in heat-related mortality and to identify factors that might explain variation across cities. Results: On average across cities, the number of deaths (per 1,000 deaths) attributable to each 10°F increase in same-day temperature decreased from 51 [95% posterior interval (PI): 42, 61] in 1987 to 19 (95% PI: 12, 27) in 2005. This decline was largest among those ≥ 75 years of age, in northern regions, and in cities with cooler climates. Although central air conditioning (AC) prevalence has increased, we did not find statistically significant evidence of larger temporal declines among cities with larger increases in AC prevalence. Conclusions: The population has become more resilient to heat over time. Yet even with this increased resilience, substantial risks of heat-related mortality remain. Based on 2005 estimates, an increase in average temperatures by 5°F (central climate projection) would lead to an additional 1,907 deaths per summer across all cities. Citation: Bobb JF, Peng RD, Bell ML, Dominici F. 2014. Heat-related mortality and adaptation to heat in the United States. Environ Health Perspect 122:811–816; http://dx.doi.org/10.1289/ehp.130739

Short-term Exposure to Particulate Matter Constituents and Mortality in a National Study of U.S. Urban Communities

Background: Although the association between PM2.5 mass and mortality has been extensively studied, few national-level analyses have estimated mortality effects of PM2.5 chemical constituents. Epidemiologic studies have reported that estimated effects of PM2.5 on mortality vary spatially and seasonally. We hypothesized that associations between PM2.5 constituents and mortality would not vary spatially or seasonally if variation in chemical composition contributes to variation in estimated PM2.5 mortality effects. Objectives: We aimed to provide the first national, season-specific, and region-specific associations between mortality and PM2.5 constituents. Methods: We estimated short-term associations between nonaccidental mortality and PM2.5 constituents across 72 urban U.S. communities from 2000 to 2005. Using U.S. Environmental Protection Agency (EPA) Chemical Speciation Network data, we analyzed seven constituents that together compose 79–85% of PM2.5 mass: organic carbon matter (OCM), elemental carbon (EC), silicon, sodium ion, nitrate, ammonium, and sulfate. We applied Poisson time-series regression models, controlling for time and weather, to estimate mortality effects. Results: Interquartile range increases in OCM, EC, silicon, and sodium ion were associated with estimated increases in mortality of 0.39% [95% posterior interval (PI): 0.08, 0.70%], 0.22% (95% PI: 0.00, 0.44), 0.17% (95% PI: 0.03, 0.30), and 0.16% (95% PI: 0.00, 0.32), respectively, based on single-pollutant models. We did not find evidence that associations between mortality and PM2.5 or PM2.5 constituents differed by season or region. Conclusions: Our findings indicate that some constituents of PM2.5 may be more toxic than others and, therefore, regulating PM total mass alone may not be sufficient to protect human health. Citation: Krall JR, Anderson GB, Dominici F, Bell ML, Peng RD. 2013. Short-term exposure to particulate matter constituents and mortality in a national study of U.S. urban communities. Environ Health Perspect 121:1148–1153; http://dx.doi.org/10.1289/ehp.120618

Effect of sequence variation in Plasmodium falciparum Histidine-Rich protein 2 on binding of specific monoclonal antibodies: Implications for rapid diagnostic tests for malaria

This Article Right arrow Full Text Right arrow Full Text (PDF) Right arrow Supplemental material Right arrow Alert me when this article is cited Right arrow Alert me if a correction is posted Services Right arrow Similar articles in this journal Right arrow Similar articles in PubMed Right arrow Alert me to new issues of the journal Right arrow Download to citation manager Right arrow Reprints and Permissions Right arrow Copyright Information Right arrow Books from ASM Press Right arrow MicrobeWorld Citing Articles Right arrow Citing Articles via HighWire Right arrow Citing Articles via Google Scholar Google Scholar Right arrow Articles by Lee, N. Right arrow Articles by McCarthy, J. Right arrow Search for Related Content PubMed Right arrow PubMed Citation Right arrow Articles by Lee, N. Right arrow Articles by McCarthy, J. Right arrow Pubmed/NCBI databases * Substance via MeSH Previous Article | Next Article Journal of Clinical Microbiology, August 2006, p. 2773-2778, Vol. 44, No. 8 0095-1137/06/$08.00+0 doi:10.1128/JCM.02557-05 Copyright © 2006, American Society for Microbiology. All Rights Reserved. Effect of Sequence Variation in Plasmodium falciparum Histidine- Rich Protein 2 on Binding of Specific Monoclonal Antibodies: Implications for Rapid Diagnostic Tests for Malaria{dagger} Nelson Lee,1,2 Joanne Baker,2 Kathy T. Andrews,1 Michelle L. Gatton,1,3 David Bell,4 Qin Cheng,2,3 and James McCarthy1* Australian Centre for International and Tropical Health and Nutrition, Queensland Institute of Medical Research and School of Population Health, University of Queensland, Queensland, Australia,1 Department of Drug Resistance and Diagnostics, Australian Army Malaria Institute, Brisbane, Australia,2 Malaria Drug Resistance and Chemotherapy, Queensland Institute of Medical Research, Queensland, Australia,3 World Health Organization, Regional Office for the Western Pacific, Manila, Philippines4 Received 8 December 2005/ Returned for modification 23 February 2006/ Accepted 26 May 2006 The ability to accurately diagnose malaria infections, particularly in settings where laboratory facilities are not well developed, is of key importance in the control of this disease. Rapid diagnostic tests (RDTs) offer great potential to address this need. Reports of significant variation in the field performance of RDTs based on the detection of Plasmodium falciparum histidine-rich protein 2 (HRP2) (PfHRP2) and of significant sequence polymorphism in PfHRP2 led us to evaluate the binding of four HRP2-specific monoclonal antibodies (MABs) to parasite proteins from geographically distinct P. falciparum isolates, define the epitopes recognized by these MABs, and relate the copy number of the epitopes to MAB reactivity. We observed a significant difference in the reactivity of the same MAB to different isolates and between different MABs tested with single isolates. When the target epitopes of three of the MABs were determined and mapped onto the peptide sequences of the field isolates, significant variability in the frequency of these epitopes was observed. These findings support the role of sequence variation as an explanation for variations in the performance of HRP2-based RDTs and point toward possible approaches to improve their diagnostic sensitivitie