A prospective study of the impact of air pollution on respiratory symptoms and infections in infants

Rationale: There is increasing evidence that short-term exposure to air pollution has a detrimental effect on respiratory health, but data from healthy populations, particularly infants, are scarce. Objectives: To assess the association of air pollution with frequency and severity of respiratory symptoms and infections measured weekly in healthy infants. Methods: In a prospective birth cohort of 366 infants of unselected mothers, respiratory health was assessed weekly by telephone interviews during the first year of life (19,106 total observations). Daily mean levels of particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3) were obtained from local monitoring stations. We determined the association of the preceding week's pollutant levels with symptom scores and respiratory tract infections using a generalized additive mixed model with an autoregressive component. In addition, we assessed whether neonatal lung function influences this association and whether duration of infectious episodes differed between weeks with normal PM10 and weeks with elevated levels. Measurements and Main Results: We found a significant association between air pollution and respiratory symptoms, particularly in the week after respiratory tract infections (risk ratio, 1.13 [1.02-1.24] per 10 μg/m(3) PM10 levels) and in infants with premorbid lung function. During times of elevated PM10 (>33.3 μg/m(3)), duration of respiratory tract infections increased by 20% (95% confidence interval, 2-42%). Conclusions: Exposure to even moderate levels of air pollution was associated with increased respiratory symptoms in healthy infants. Particularly in infants with premorbid lung function and inflammation, air pollution contributed to longer duration of infectious episodes with a potentially large socioeconomic impact.

Air pollution during pregnancy and neonatal outcome: a review

There is increasing evidence of the adverse impact of prenatal exposure to air pollution. This is of particular interest, as exposure during pregnancy--a crucial time span of important biological development--may have long-term implications. The aims of this review are to show current epidemiological evidence of known effects of prenatal exposure to air pollution and present possible mechanisms behind this process. Harmful effects of exposure to air pollution during pregnancy have been shown for different birth outcomes: higher infant mortality, lower birth weight, impaired lung development, increased later respiratory morbidity, and early alterations in immune development. Although results on lower birth weight are somewhat controversial, evidence for higher infant mortality is consistent in studies published worldwide. Possible mechanisms include direct toxicity of particles due to particle translocation across tissue barriers or particle penetration across cellular membranes. The induction of specific processes or interaction with immune cells in either the pregnant mother or the fetus may be possible consequences. Indirect effects could be oxidative stress and inflammation with consequent hemodynamic alterations resulting in decreased placental blood flow and reduced transfer of nutrients to the fetus. The early developmental phase of pregnancy is thought to be very important in determining long-term growth and overall health. So-called "tracking" of somatic growth and lung function is believed to have a huge impact on long-term morbidity, especially from a public health perspective. This is particularly important in areas with high levels of outdoor pollution, where it is practically impossible for an individual to avoid exposure. Especially in these areas, good evidence for the association between prenatal exposure to air pollution and infant mortality exists, clearly indicating the need for more stringent measures to reduce exposure to air pollution.

Lake Ladoga: Water Resources for the Sustainable Development of North-Western Russia and Finland

The aim of this project was to evaluate the present state and possible changes of water resources in Lake Ladoga and its drainage basin for the purposes of the sustainable development of North-Western Russia and Finland. The group assessed the state of the water resources in quantitative and qualitative terms, taking the system of sustainable development indicators suggested by the International Commission on Sustainable Development as a basis for assessment. These include pressure indicators (annual withdrawals of ground and surface water, domestic consumption of water per capita), state indicators (ground water reserves, concentration of faecalcoliform in fresh water, biochemical oxygen demand), and response indicators (waste-water treatment coverage, density of hydrological networks). The group proposed the following additional indicators and indices for the complex evaluation of the qualitative and quantitative state of the region's water resources: * Pressure indicators (external load, coefficient of anthropogenic pressure) * State indicators and indices (concentrations of chemicals in water, concentrations of chemicals in sediments, index of water pollution, critical load, critical limit, internal load, load/critical load, concentration/critical limit, internal load/external load, trophic state, biotic indicators and indices) * Response indicators (discharges of pure water, polluted water, partly treated water and the ratio between these, trans-boundary fluxes of pollutants, state expenditure on environmental protection, human life span) The assessment considered both temporal and spatial aspects and produced a regional classification of the area according to the index of water pollution. Mathematical models were developed to describe and forecast the processes under way in the lake and can be used to estimate the influence of climatic changes on the hydrological regime, as well as the influence of anthropogenic load on the trophic state of Lake Ladoga and to assess the consequences of accidental discharges of polluting admixtures of different kinds into the lake. The results of this mathematical modelling may be of use to decision-makers responsible for the management of water resources.

Cardiac troponins as indicators of acute myocardial damage in dogs

Cardiac troponin I (cTnI) and T (cTnT) have a high sequence homology across phyla and are sensitive and specific markers of myocardial damage. The purpose of this study was to evaluate the Cardiac Reader, a human point-of-care system for the determination of cTnT and myoglobin, and the Abbott Axsym System for the determination of cTnI and creatine kinase isoenzyme MB (CK-MB) in healthy dogs and in dogs at risk for acute myocardial damage because of gastric dilatation-volvulus (GDV) and blunt chest trauma (BCT). In healthy dogs (n = 56), cTnI was below detection limits (<0.1 microg/L) in 35 of 56 dogs (reference range 0-0.7 microg/L), and cTnT was not measurable (<0.05 ng/mL) in all but 1 dog. At presentation, cTnI, CK-MB, myoglobin, and lactic acid were all significantly higher in dogs with GDV (n = 28) and BCT (n = 8) than in control dogs (P < .001), but cTnT was significantly higher only in dogs with BCT (P = .033). Increased cTnI or cTnT values were found in 26 of 28 (highest values 1.1-369 microg/L) and 16 of 28 dogs (0.1-1.7 ng/mL) with GDV, and in 6 of 8 (2.3-82.4 microg/L) and 3 of 8 dogs (0.1-0.29 ng/mL) with BCT, respectively. In dogs suffering from GDV, cTnI and cTnT increased further within the first 48 hours (P < .001). Increased cardiac troponins suggestive of myocardial damage occurred in 93% of dogs with GDV and 75% with BCT. cTnI appeared more sensitive, but cTnT may be a negative prognostic indicator in GDV. Both systems tested seemed applicable for the measurement of canine cardiac troponins, with the Cardiac Reader particularly suitable for use in emergency settings.

Locally generated particulate pollution and respiratory symptoms in young children

BACKGROUND: Particulate matter <10 mum (PM(10)) from fossil fuel combustion is associated with an increased prevalence of respiratory symptoms in children and adolescents. However, the effect of PM(10) on respiratory symptoms in young children is unclear. METHODS: The association between primary PM(10) (particles directly emitted from local sources) and the prevalence and incidence of respiratory symptoms was studied in a random sample cohort of 4400 Leicestershire children aged 1-5 years surveyed in 1998 and again in 2001. Annual exposure to primary PM(10) was calculated for the home address using the Airviro dispersion model and adjusted odds ratios (ORS) and 95% confidence intervals were calculated for each microg/m(3) increase. RESULTS: Exposure to primary PM(10) was associated with the prevalence of cough without a cold in both 1998 and 2001, with adjusted ORs of 1.21 (1.07 to 1.38) and 1.56 (1.32 to 1.84) respectively. For night time cough the ORs were 1.06 (0.94 to 1.19) and 1.25 (1.06 to 1.47), and for current wheeze 0.99 (0.88 to 1.12) and 1.28 (1.04 to 1.58), respectively. There was also an association between primary PM(10) and new onset symptoms. The ORs for incident symptoms were 1.62 (1.31 to 2.00) for cough without a cold and 1.42 (1.02 to 1.97) for wheeze. CONCLUSION: In young children there was a consistent association between locally generated primary PM(10) and the prevalence and incidence of cough without a cold and the incidence of wheeze which was independent of potential confounders.

The National Morbidity, Mortality, and Air Pollution Study Database in R

The NMMAPS data package contains daily mortality, air pollution, and weather data originally assembled as part of the National Morbidity,Mortality, and Air Pollution Study (NMMAPS). The data have recently been updated and are available for 108 United States cities for the years 1987--2000. The package provides tools for building versions of the full database in a structured and reproducible manner. These database derivatives may be more suitable for particular analyses. We describe how to use the package to implement a multi-city time series analysis of mortality and PM(10). In addition we demonstrate how to reproduce recent findings based on the NMMAPS data.

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.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

Seasonal Analyses of Air Pollution and Mortality in 100 U.S. Cities

Time series models relating short-term changes in air pollution levels to daily mortality counts typically assume that the effects of air pollution on the log relative rate of mortality do not vary with time. However, these short-term effects might plausibly vary by season. Changes in the sources of air pollution and meteorology can result in changes in characteristics of the air pollution mixture across seasons. The authors develop Bayesian semi-parametric hierarchical models for estimating time-varying effects of pollution on mortality in multi-site time series studies. The methods are applied to the updated National Morbidity and Mortality Air Pollution Study database for the period 1987--2000, which includes data for 100 U.S. cities. At the national level, a 10 micro-gram/m3 increase in PM(10) at lag 1 is associated with a 0.15 (95% posterior interval: -0.08, 0.39),0.14 (-0.14, 0.42), 0.36 (0.11, 0.61), and 0.14 (-0.06, 0.34) percent increase in mortality for winter, spring, summer, and fall, respectively. An analysis by geographical regions finds a strong seasonal pattern in the northeast (with a peak in summer) and little seasonal variation in the southern regions of the country. These results provide useful information for understanding particle toxicity and guiding future analyses of particle constituent data.

MORTALITY IN THE MEDICARE POPULATION AND CHRONIC EXPOSURE TO FINE PARTICULATE AIR POLLUTION

Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

Monitoring pollution in river Mure , Romania, Part III: biochemical effect markers in fish and integrative reflection

Along a downstream stretch of River Mure , Romania, adult males of two feral fish species, European chub (Leuciscus cephalus) and sneep (Chondrostoma nasus) were sampled at four sites with different levels of contamination. Fish were analysed for the biochemical markers hsp70 (in liver and gills) and hepatic EROD activity, as well as several biometrical parameters (age, length, wet weight, condition factor). None of the biochemical markers correlated with any biometrical parameter, thus biomarker reactions were related to site-specific criteria. While the hepatic hsp70 level did not differ among the sites, significant elevation of the hsp70 level in the gills revealed proteotoxic damage in chub at the most upstream site, where we recorded the highest heavy metal contamination of the investigated stretch, and in both chub and sneep at the site right downstream of the city of Arad. In both species, significantly elevated hepatic EROD activity downstream of Arad indicated that fish from these sites are also exposed to organic chemicals. The results were indicative of impaired fish health at least at three of the four investigated sites. The approach to relate biomarker responses to analytical data on pollution was shown to fit well the recent EU demands on further enhanced efforts in the monitoring of Romanian water quality.