Quantifying the short-term effects of air pollution on health in the presence of exposure measurement error: A simulation study of multi-pollutant model results

Background: Most epidemiological studies estimate associations without considering exposure measurement error. While some studies have estimated the impact of error in single-exposure models we aimed to quantify the effect of measurement error in multi-exposure models, specifically in time-series analysis of PM2.5, NO2,and mortality using simulations, under various plausible scenarios for exposure errors. Measurement error in multi-exposure models can lead to effect transfer where the effect estimate is overestimated for the pollutant estimated with more error to the one estimated with less error. This complicates interpretation of the independent effects of different pollutants and thus the relative importance of reducing their concentrations in air pollution policy. Methods: Measurement error was defined as the difference between ambient concentrations and personal exposure from outdoor sources. Simulation inputs for error magnitude and variability were informed by the literature. Error-free exposures with their consequent health 16outcome and error-prone exposures of various error types (classical/Berkson) were generated. Bias was quantified as the relative difference in effect estimates of the error-free and error-prone exposures. Results: Mortality effect estimates were generally underestimated with greater bias observed when low ratios of the true exposure variance over the error variance were assumed (27.4% 21underestimation for NO2). Higher ratios resulted in smaller, but still substantial bias (up to 19% for both pollutants).Effect transfer was observed indicating that less precise measurements for one pollutant (NO2) yield more bias, while the co-pollutant(PM2.5) associations were found closer to the true. Interestingly, the sum of single-pollutant model effect estimates was found closer to the summed true associations than those from multi-pollutant models, due to cancelling out of confounding and measurement error bias. Conclusions: Our simulation study indicated an underestimation of true independent health effects of multiple exposures due to measurement error. Using error parameter information in future epidemiological studies should provide more accurate concentration-response functions

Profiling SO2 air pollution patterns in 9 EU Aphekom cities: The Aphekom Project

A detailed analysis of hourly pollutant concentrations mainly focusing on SO2 data obtained from 9 centres involved in the Aphekom project was conducted. This involved the generation of individual diurnal SO2 profiles in order to: (i) identify city specific patterns including source apportionment and quantification, (ii) track changes over time, (iii) analyse the changes in SO2 concentrations from different emission sources, i.e. traffic, heating, shipping and industrial sources, overtime

Mortality impacts of sulphur concetrations in 20 European cities in the APHEKOM Project

The implementation of three EU directives to reduce sulphur content in fuel was assessed for mortality impacts in 20 European cities, between 1990 and 2007 in the APHEKOM project. This specific study aimed to examine whether different lag structures apply to the relationships between cardiovascular and respiratory events and SO2 concentrations, which will therefore result in differences in mortality impacts from regulation implementation. Prior evidence has shown that cardiovascular mortality is more likely to be affected by SO2 concentrations on the same or the previous day of the event, while respiratory mortality more likely to show a delayed effect of exposure to the same pollutant

Atmospheric circulation types and daily mortality in Athens, Greece.

We investigated the short-term effects of synoptic and mesoscale atmospheric circulation types on mortality in Athens, Greece. The synoptic patterns in the lower troposphere were classified in 8 a priori defined categories. The mesoscale weather types were classified into 11 categories, using meteorologic parameters from the Athens area surface monitoring network; the daily number of deaths was available for 1987-1991. We applied generalized additive models (GAM), extending Poisson regression, using a LOESS smoother to control for the confounding effects of seasonal patterns. We adjusted for long-term trends, day of the week, ambient particle concentrations, and additional temperature effects. Both classifications, synoptic and mesoscale, explain the daily variation of mortality to a statistically significant degree. The highest daily mortality was observed on days characterized by southeasterly flow [increase 10%; 95% confidence interval (CI), 6.1-13.9% compared to the high-low pressure system), followed by zonal flow (5.8%; 95% CI, 1.8-10%). The high-low pressure system and the northwesterly flow are associated with the lowest mortality. The seasonal patterns are consistent with the annual pattern. For mesoscale categories, in the cold period the highest mortality is observed during days characterized by the easterly flow category (increase 9.4%; 95% CI, 1.0-18.5% compared to flow without the main component). In the warm period, the highest mortality occurs during the strong southerly flow category (8.5% increase; 95% CI, 2.0-15.4% compared again to flow without the main component). Adjusting for ambient particle levels leaves the estimated associations unchanged for the synoptic categories and slightly increases the effects of mesoscale categories. In conclusion, synoptic and mesoscale weather classification is a useful tool for studying the weather-health associations in a warm Mediterranean climate situation

Vitamins A, C and E and the risk of breast cancer: results from a case-control study in Greece

Although several dietary compounds are hypothesized to have anticarcinogenic properties, the role ofpecific micronutrients in the development of breast cancer remains unclear. To address this issue, we assessed intake of retinol, β-carotene, vitamin C and vitamin E in relation to breast cancer risk in a case–control study in Greece. Eight hundrednd twenty women with histologically confirmed breast cancer were compared with 1548 control women. Dietary data were collectedhrough a 115-item semiquantitative food frequency questionnaire. Data were modelled by logistic regression, with adjustment forotal energy intake and established breast cancer risk factors, as well as mutual adjustment among the micronutrients. Amongost-menopausal women, there was no association between any of the micronutrients evaluated and risk of breast cancer. Amongremenopausal women, β-carotene, vitamin C and vitamin E were each inversely associated with breast cancer risk, but afterutual adjustment among the three nutrients only β-carotene remained significant; the odds ratio (OR) for a one-quintilencrease in β-carotene intake was 0.84 (95% confidence interval 0.73–0.97). The inverse association observed with β-carotene intake, however, is slightly weaker than the association previously observed with vegetable intake in these data,aising the possibility that the observed β-carotene effect is accounted for by another component of vegetables. ©1999 Cancer Research Campaig

Personal exposure to air pollution and respiratory health of COPD patients in London

Previous studies have investigated the effects of air pollution on chronic obstructive pulmonary disease (COPD) patients using either fixed site measurements or a limited number of personal measurements, usually for one pollutant and a short time period. These limitations may introduce bias and distort the epidemiological associations as they do not account for all the potential sources or the temporal variability of pollution.We used detailed information on individuals' exposure to various pollutants measured at fine spatio-temporal scale to obtain more reliable effect estimates. A panel of 115 patients was followed up for an average continuous period of 128 days carrying a personal monitor specifically designed for this project that measured temperature, PM10, PM2.5, NO2, NO, CO and O3 at one-minute time resolution. Each patient recorded daily information on respiratory symptoms and measured peak expiratory flow (PEF). A pulmonologist combined related data to define a binary variable denoting an "exacerbation". The exposure-response associations were assessed with mixed-effects models.We found that gaseous pollutants were associated with a deterioration in patients' health. We observed an increase of 16.4% (95% confidence interval: 8.6-24.6%), 9.4% (5.4-13.6%) and 7.6% (3.0-12.4%) in the odds of exacerbation for an interquartile range increase in NO2, NO and CO respectively. Similar results were obtained for cough and sputum. O3 was found to have adverse associations with PEF and breathlessness. No association was observed between particles and any outcome.Our findings suggest that, when considering total personal exposure to air pollutants, mainly the gaseous pollutants affect COPD patients' health

The association of fat and other macronutrients with breast cancer: a case-control study from Greece.

The Greek diet is characterized by a high total fat but low saturated fat intake. In a hospital-based case-control study of female breast cancer conducted in Athens (1989-91), 820 patients with confirmed cancer of the breast were compared with 795 orthopaedic patient controls and 753 hospital visitor controls, matched to the cases by age and interviewer. Diet was ascertained through a semiquantitative food frequency questionnaire; macronutrient intakes were estimated from the nutrient content of a selected typical portion size for each specified food item, summed for all items. Logistic regression was used to analyse the data, controlling for demographic and reproductive risk factors for breast cancer as well as for total energy intake and mutual confounding influences among nutrients. There was no significant or suggestive association of total protein, total fat, categories of fat or total carbohydrates with breast cancer risk. Thus, the mutually adjusted relative risk per quintile and (in parenthesis) 95% confidence interval were: for protein, 1.06 (0.94-1.20); saturated fat, 0.99 (0.89-1.11); monounsaturated fat, 0.97 (0.88-1.07), polyunsaturated fat, 1.05 (0.97-1.13); and total carbohydrates, 1.03 (0.94-1.12). In alternative analytical approaches only total protein appeared to be positively associated to the occurrence of breast cancer with some consistency, but the results were far from statistically significant. These findings do not support a role for fat or other energy-generating nutrients in the aetiology of breast cancer